ANALYTICAI, DESIGN OF A PARALLEL HYBRID ELECTRIC

POWERTRAIN FOR SPORTS UTILITY VEHICLES AND HEAVY

TRUCKS

A Thesis Presented to

The Faculty of the

Fritz J. and Dolores H.Russ College of Engineering and Technology

Ohio University

In Partial Fulfillment

Of the Requirement for the Degree

Master of Science

by

Madhava Rao Madireddy

March. 2003

OHIO UNIVERSITY LIBRARY

l a h l e of' Contents:

Chapter 1 Introduction 6: Bachgl-ound

1 1 Iiltroductio~l

1 2 Purpose of Research

1 3 Ser~es and Parallel Hybrid Electric Vehicles

Chapter 2 Literature Review

2.1 Currellt State of ai-t in Hybrid Electric Vehicles

2 1.1 Production HEVs available for purchase 111 inoclel year 2001

2 1 2 Efforts of Big Three for I-Iybi-idization of SUVs, cars and trucks

2.1 3 Current Research and Developlneilt efforts for Hybridization

of SlJVs

2 1 3 Cu1-1-ent Research and developinent efforts for Hybridization

of heavy vehicles

2 2 S~inulatioil Software for HEVs

2 3 Related Research Work

2 3 Hqbridl~ation studies Using ADVISOR

Chapter 3 I~itroduction to ADVISOR

3 1 l~ltroduction to ADVISOR

3 2 LTsiilg ADVISOR

3 2 i Defining a Vehicle

3 2 2 Ruil~li~lg a Simulatioll

3.2.3 Lookii~g at Results

Chapter 4 Powertrain Specifications

4.1 Scaling the Vehicle Cornpollents

4.2 Engine, Motor and Battery Specifications

4.2 1 SUV SI Engine Specifications

4.2.2 Heavy Truck CI Eilgille Specifications

4.2.3 Motor Specifications

4.2.4 Battery Specificatioils

4.2.5 The problem of SOC

Chapter 5 Design Methodology

5.1 Overall goal of the study

5.2 Design Teclmique elnployed

5.2.1 Teclx~ical Optimizatioil

5.2.2 Cost Based Optiniization

Chapter 6 Simulation, Results and Conclusion

6 . 1 Control Strategy enlployed

6.2 Simulation and results for average SUV

6.3 Simulation and results for full-size SUV

6.4 Simulation and results for heavy trucks

6.5 Conclusio~l

6.6 Recomil~endations for fui-ther si~liulat~on studies

References

Bibliography and Recommended Readings

Appendices

ADVISOR Documentatioll

JIatlab Files

List of Figures:

1.1 Series Hybrid Electric Vehicle

1.2 Parallel H~.brid Electric Vehicle

2 2 Toljota Pnus

2 3 Diii~nler Clxysler Citadel

2 4 Dailnler Cluysler ESX3

2 5 Ford Escape HEV

1.6 The GM Precept

2.7 Llitsubishi HV

2 .8 Nissan Tino HEV

2.9 Dodge Duranyo

2.10 Ford Prodigy

2.1 1 Transit Bus

2.12. Sterling AT 2500

2.13 Kelln ol-th 800

3.1 Vehicle Input Figure in ADVISOR

3 2 Sinlulation Set Up Figure in ADVISOR

3 3 ADVISOR Results Figure

4.1 SI Engine Torque Speed Characteristics

4 7 Cl Engine Torque Speed Characteristics

4.3 4Zotor Torque Speed Characteristics

vii

4 .3 Panasonic 12V/3SA4HR Sealed Lead Acid battery 3 7

4.5 Battery Open Circuit Voltage Characteristics 4 0

4.5 Battery Instalitaneous Power vs. SOC 4 1

6.1 Federal Test Procedure (FTP) Drive Cycle 47

6.2 Fuel Econoniy (mpg) vs. percent hybridization for an average SLY 49

6.3 Acceleration tinie (0 60111ph) VS. percent hybridization @ different charge 50

capacities of tlie batteries for an average SUV

6.3 Net Value (Combined Fuel Econoniy and Perfomn~ance) vs. percent 5 1

llybridization for an average SUV

6.5 Cost of Average SUV vs. percent hybridization. 5 2

6.6 Components of Cost Optimization for average SLY with 25 battery lilodules 53

6.7 Net Value with Cost Consideration vs. percent hybridization 51

6.8 Coillparison of Teclu~ical and Cost Optiiliizatio~ls for average Sb'V with 55

25 battery n~odules

6.9 Colnpollellts of Cost Opti~liizatioii for average SLV with 25 battery 56

modules and with low cost batteries

6.10 The Effect of Low Cost Batteries for an average SUV 5 7

6.1 1 (a) Teclulical Ket Value Change due to tlie variation in Weighing Factors 58

6.11 (b) Cost Optimized h'et Value Cl-iange due to the variation in 5 9

Weighing Factors

6.12 Fuel Economy (mpg) vs. percent hybridization for full size SUV 6 1

6.13 .4cceleration time vs. percent hybridization for full size SLV 6 1

. . . V l l l

6.14 Net Value (Teclmical) vs. percent hybridization for full size SLV

6.15 Cost of f~lll size SUV vs. percent h~~bridization for full size SLW

6.16 Componeilts of Cost Optiillizatioil for full size SUV with 25 n~odules

6.17 Net Value (Cost Optimization) vs. percent hybridization for Full size SUV

6.18 Components of Cost Optinlization for full size SLW with 25 nlodules

6.19 JiYINTER Drive Cycle

6 20 Fuel Economy (inpg) vs. percent hybridization for heavy trucks

6.21 .Acceleration tiine (0 6O111ph) vs. percent l~ybridization for heavy trucks

6.23 Set Value (Technical Optimization) vs. percent hybridization for heavy

trucks

6.23 Cost of heavy truck vs. percent hybridization.

6.24 Co~llpoilents of Cost Optiillization for heavy tiuck

6.25 Net V a l ~ ~ e (Cost Optimization) vs. percent hybridization for heavy trucks

6.26 Components of Cost Optimization for heavy tn~cl i with low cost batteries

6.27 Effect of low cost batteries on the net value of heavy truck

A.1 .\cceleration Test Ada anced Optioils window

A 2 Pdrainetrlc Results Figure in L4D\71SOR

List of Tables:

6.1 Results from ADVISOR for a 150kW powered average SUV

6.2 Results from ADVISOR for a 200KW powered Full Size SUV

6.3 Results from ADVISOR for a 400 KW powered heavy truck

S ~ m b o l s and Abbreviations:

ADVISOR Advanced Vehicular Simulator

APC Auxiliary Power Unit

A 11

C I

DOE

Elph

EP.4

EV

FTP

HEV

HV

HVEC

1 C

ICE

MPG

1IPH

PKGV

SI

soc SLV

TDES

UDDS

V Elph

SULEV

ZEV

Ampere Hour

Colnpressio~l Ignition

Department of Energy

Electrically Peaking Hybrid

Envirolu~~ental Protection Agency

Electric Vehicle

Federal Test Procedure

Hybrid Electric Vehicle

Hybrid Vehicle

Hybrid Vehicle Evaluation Code

Internal Combustion

Intelnal Combustioll Ellgiile

Miles Per Gallon (gasoline equivalent)

Miles Per Hour

Partnership of New Generation of Vehicles

Spark Ignition

State of Charge

Sports Utility Vehicles

Turbo Diesel Engine Sin~ulatio~l

Urban Dynamometer Driving Schedule

Versatile Electrically Pealting Hybrid

Super Ultra Low E~nission Vehicle

Zero Emission Vehicles

Chapter 1:

Introduction C ! Background

1.1 Introduction

Con\.entional internal combustion (IC) engine driven power trains have several

disadvantages that negatively affect fuel economy and en~issions. Specifically, IC engines

;Ire tqpically oversized by roughly ten times to meet perfolmance targets, such as

acceleration and starting gradeability (Moore, 1996). This moves the cruising operating point

away from the optimal operation point (Gao et al., 1997). Moreover, an engine cannot be

optimized for all the speed and load ranges under which it must operate (Moore, 1996). One

viable solution to these problems is the use of a hybrid electric power train that decouples the

IC engine fi-om peak requirements, thus reducing the demands on the engine map.

1.2 Purpose of the Research:

In the conventional veliicles~ the entire power is derived from the IC engine. The fuel

economy can be in~proved if we replace a part of the power by the motor powered by the

batteries. But the initial purchase cost will shoot up because of the batteries and motor. The

percentage of the n~o to r power out of the total power is defined as Percent Hybridization.

The basic objective of this study is to ai-rive at a percent hybridization for a considered power

Ie\ el to trade off fuel econonly with perf01-mance (ability to accelerate quickly: g-adeability)

2nd initial cost of the vehicle.

1.3 Series and Parallel E-IEV's

A hybl-id electric vehicle (HEV) combines at least t\?fo sources of propulsion, one of

them being electric. Hybrid power production options include spark ignition engines,

colllpression igilition direct illjectioil engines, gas turbines, and fuel cells. The primary

options for energy storage include batteries, ultra capacitors, and f l p h e e l s .

-4 typical hybrid electric \,chicle combines the illtenla1 conlbustion engine of a

con~.entional vehicle with the batteries and electric motor of an electric vehicle. There are

tlpically hvo configurations of hybrid electric vehicles. They are series and parallel.

In a serles l ~ y b n d electnc ~ e h i c l e (Fig 1 I), the nlotor dnhes the uheeis and the

intenla1 col~lbustloil engine IS not connected to the 1511eels hvith any mechanical connection

Generator Motor 'Controller

Fig 1.1 Series Hybrid Electric Vehicle

All the drive to the wheels is supplied from the electric lllotor that is supplied ~vit11 power

fro111 the batteries. The batteries ixay be cl~arged by the internal con~bustion engine. The

pon,zr unit or rhe IC engil~e in series hybrid electric vehicle is efficient with lower emissions

3

than thaz in a parallel hybrid because ~t can operate constantly at its optinlum effic~encq point

since ir is conipletely decoupled fro111 the load. However, the series hybrids drive lll<e an

electnc car ~ . i t h an extended range and not like conventional cars. This is not necessal-ily

bad. but it is unfamiliar and cui~ent ly consuii1ers prefer the driving feel of conventional

~ieliicles and parallel HEVj over series HE1.s.

In a parallel hybrid drive train (Fig 1.2), the intel-iial combustion unit and the electsic

motor run in parallel.

1'tnlir-r llrvl

F1g1.2 Parallel I-Iybrid Electric Vehicle

Both tlie engine and the electric inotor are co~liiected to the trailsmission indepe~idently.

-4s a resulr, in a parallel hybrid, both the electric motor and the IC eilgille can provide

prop~~lsiol l power. Depending on the power requirellleiit and tlie state of charge of the

batteries, the coiltrol system tu1-11~ the motor on or off. The motor is powered by the batteries.

n.hich may be charged f i -on~ an e s t e~ua l power supply or the IC engine. The IC engine in a

parsllrl HEV can be designed for the operation in the cruising range and the batteries via a

4

motor call provide suppleilieiltary power for the vehicle during initial acceleration and

gradeability (moviilg along a gradient or uphill) requirements. Tlie i ~ ~ o t o r acts as a generator

to recapture tlie braking energy and charges the batteries. In case of overheating, the IC

engine can even be tuilled off because there is an auxiliary power source for prop~llsion

(though for a liiliited range). The parallel hybrid electric drive train perfoims similar to a

ion\.e~itional vehicle drive train as the engine is directly connected to the transmission.

Coiisumers call have the driving feel of a conr~entional vehicle and hence tlie manufacturers

caii nlarket this easily.

The parallel electric assist control strategy eiilployed by ADVISOR uses the iilotor for

additional poLver when needed by the vehicle and rnaiiltaiils charge in the batteries.

The parallel assist strategy can use the electric inotor in a variety of ways:

1 . The niotor caii be used for all driving torque below a certain minimun~ veliicle speed.

2 . The motor is used for torque assist if the required torque is greater than the maximum

producible by tlie eligiile at the engine's operating speed.

3. Tlie motor charges the batteries by regenerative braking.

4. When the engine would run i~iefficieiltly at the required engine torque at a given

speed, the eiigiile will shut off and the lnotor will produce the required torque.

5 . Lt11en tlie battery SOC is low, the e1lgi11e will provide excess torque which will be

used by the iiiotor to charge tlie battery.

As tlie hybridization a l l o ~ . s the IC engiiies be designed more fuel efficient? tlie

emissions wliich are the results of iiicolliplete coiilbustioil caii be cut down. Tliis could help

7 d

to a c l ~ l e ~ ~ e the goals of Partnership of h'ew Generat1011 of Vehicles (PUGV). a joint effolt b)

United States Go~eri l lnent and sonle automotlbe lnanufacturing filnis Hybrlds M 111 necer be

t n ~ e zero emission vehicles (ZEV), however, because of their intellla1 conibustioi? engine.

Even the electric veliicles are not really ZEVs because of the eniissioils during the energ),

son\.ersion required to charge the batteries. Hybrid power systems can coliipensate for the

sllortfall in battery technology. Because batteries could supply only e n o u ~ h energy for short

tsips, an onboal-d generator, pou,ered by an intellla1 coinbustion engine. could be installed

niid used for longer trips. This is similar to tlie series coilfiguratioil and is called a range

extender.

Hybricl Electric vehicles a?-e cu~~-ent ly gaining a lot of attenti011 of manufacturers d ~ l e

to the environmental and federal laws for regulated emissions. The h>~brid's c o n ~ p l e s ~ t y and

tlie cost and size o f the batteries are the biggest hill-dles in rnarlieting these vehicles. Tl~oilgh

the hybrid vehicle may have higher initial cost compared to a con\.entional \.chicle, the

sa\,ings in f~ ie l econol~ly cut d0u.n tlie long teiin operating cost.

Organization of the Thesis:

Cliapter 2 gibes an lntroductiol~ to the cul-rent state of art of the hybrid electric

vehicle and tlie simulation tools developed aiid used by different orga~lizations to predict and

test the perfoilllaiice of the vehicles. Cliapter 3 introduces the s o h ~ a r e tool called

ADVISOR. Chapter 3 gives specifications of the pov,.el-train used for simulation. Chapter 5

gives tlie design methodology emploq-ed in this study. Chapter 6 gi\-es the siillulatio~l resi~lts

of fuel economy- ;liid pe~- fo~~ i i ance for different vehicle platforills and also summarizes the

iesults and gives col~clusloiis and discussions and scope for future research

Chapter 2:

Literature Review

2.1 Current State of Art in Hybrid Electric Vehicles

This thesis investigates the hybridization of sports utility vehicles and large tnlcks

for potential fuel economy improvements without significant cost or performance penalties.

A large amount of research and developnlent has already been completed by the automotive

industry for hybridizing passenger cars, and a limited number of development programs are

also undeluay for hybridizing light to heavy duty vehicles. This section presents a review of

existing hybrid vehicle programs to be used as a baseline for the analytical research

presented later in this thesis report.

2.1.1 Production HEVs available for purchase in model year 2001.

The I-Ionda Insight (Fig 2.1) is available to United States consumers now, and so far

it's been getting a lot of attention.

Fig 2.1 Hollda Insight

It is a series hybrid with high fuel econollly averaging 70 miles per gallon of gasoline in

co~nbined city and highway driving. This figure of 70 mpg considers fuel use only and does

not include the battery charge used during the drive since that charge is replenished durlng

operation.

7

The Insight uses ail SI engine as its 111aili power source with a peak power of 671ip@

5700rpm and a peak torque of 661b ft @4800rpm. The hybrid power source is a penuanent

magnet DC brushless motor which can generate 10kW @ 3000rp1ii. Energy storage is

PI-ovided by Nickel Metal Hydride batteries of 144v (120 cells a 1 . 2 ~ each) at 6.5AH rated

capacity. Tlie percent hybridization employed is 20% (Engine power/ruotor power is 4 : 1 ) .

The Environmental Protection Agency (EPA) has certified the Insight as a S i~per Ultra Low

Emission Vehicle (SULEV).

The Toyota P r i ~ ~ s (Fig 2.2), wliicli calue out in Japan at the end of 1997, is designed

to reduce emissions in urban areas.

Fig 2.2 'Toyota Prius

It meets Califonlia's super ~ ~ l t r a low emissions vehicle (SULEV) standard. Tlie IC

engine has a peak power of 70 lip @4500rpm and a peak torque of 82 Ib ft @ 4200rp111. The

PI -~LIS uses a permanent magnet lliotor as its hybrid power source with a peak power of 44lip

available from 1040 rp~ii tllro~lgh 5600 rplii and a peak torq~le of 258 lb ft from 0 to 400 rpm.

Tlie percent hybridization for the Prius is 30%. Siliiilar to the Insight, the Prius also uses

sealed nickel nistal Iiydride batteries witli a total o u t p ~ ~ t of 2 7 3 . 6 ~ (228 1 . h cells). [I]

2.1.1 EfTorts of Big Three for the hybridization of SLVs, cars and trucks

None of the Big Three US automakers (Ford, General Motors, and DaimlerChrysler)

cui-rently have hybrid vehicles available for sale, but all have active hybrid vehicle research

progi-an~s for both passenger cars and light duty trucks. Some examples of hybrid passenger

cars in development are discussed below.

Dairnler Chrysler Citadel (Fig 3.3) uses a gasoline fed 3.5 liter V 6 engine to power

tlie rear hvheels while the front wheels are powered by an electric motor. The engine delivers

7531ip and the motors 7011p for a percent hybridization of 2201;. The fuel economy

preclictions are not available in the ai-ticle. [ 2 ]

Fig 2.3 Dainller Chrysler Citadel

Tile Daillller Chi-ysler ESX3 (Fig 2.4) is a mild hybrid with has a starter! generator

designed for new 42 Volts systems. Its electric powel~raiii combines a clean, efficient diesel

engiile, electric motor and state of the art lithium ion battery to achieve an average 72 miles

1121. gallon (3.3 liters/100 knl) fuel efficiency (gasoline equivalent). This is close to PNGVs

goal of SO nlpg (2.9 liters/100 kni) family vehicles.

Fig 2 .3 Daiiiller Chiysler ESX3

Tlis Ford Escape HEV (Fig 2.5), which will make its debut in 2003 ~vil l feahlre an

electric dri~,etrain to augment its fuel efficient four cylinder gasoline engine. Escape HE\.

will be especially fuel efficient in the city, delivering about 40 mpg in urban dri\.ing. Yet the

Escape I-I€\' \\.ill dsliver acceleration perfomiaiice similar to an Escape equipped ~vitli V 6

engine. The hybrid Escape will be capable of being driven more than 500 miles oil a single

t ad< of gasoli11e and will be certified as a super ultra low eniission vehicle (SULEJ') under

Calil'o~ilir! enlissioils standards and meet Stage I\: requirelilents in Europe before the)

become mandatorq~ in 2005. The power ratings of the engine, batteries and motor are not

~i\.r!ilable fi-om tile source. [3]

Fig 2.5 Ford Escape HEV

G*M is planning to develop the GM Precept (Fig 2.61, a 5 passenger iehicle Power

for tlie Precept. a hybrid; is supplied to the fioont wheels by a battery powered electric traction

s)item. 4 lightweight, 1.3 liter, three cylinder diesel engine ivith turbocharged comprrssion

igiiition is moonted in the rear. The power ratings of the engine and motor are not available

from the source. [3]

Fig 2.6 GM Precept

The Mitsubishi (Fig 2.7) is a HEV powered by electricity and recharged ivitb on on

board. gasoline fileled, auxiliary power unit (APU).

Fig 2.7 Mitsubishi HV

Tn.in electrical engines drive the front wheels, using one for lower speeds and both

for acceleration, which allows theill to run within their most efficient operating range.

Cnder nol~ilal driving conditions the electrical engines are powered by 28 open cell batteries.

If the battery charge falls below half its capacity the APU switches on and begins to charge

the batteries. The APU is a 1.5 liter, four cylinder; water cooled, four stroke, gasoline fueled

engine \\.it11 a l~iglily efficieilt AC power generator. Once the charge is restored to above

G O 0 ; , operation autoinatically retullls to battery mode. This vehicle has a range of nlore than

150 miles, the capability to travel at speeds up to 95 mph, and registers exhaust elnissions of

11e~11.ly zero. The HEV features fi-ont wheel drive and a two speed semiautomatic

transmission. The power ratings of the engine and motor are not available from the source.

[31

The Nissan Tino (Fig 2.8) is powered by a combination of a 1.8 liter foiir cylinder

engine and an electlic motor with lithium ion batteries. The vehicle is a five passenger car

that achieves t~vice the fuel econonly and 50% less eillissions than a coilventional vehicle of

the same type. The power ratings are not available from the source. [3]

Fig 2.8 Kissail Tino HEV

2.1.3 Curre~lt Research and Development efforts for Hybridization of SUVs

Numerous SUV and light truclc l~ybridization efforts are under way and could greatly

inlpact the national file1 use and emissions because the demand for SUVs is large and the

fuel ecoiloiily of the SUV propelled by the conventional drive train is poor. The f~lel

econoniy and elllissioils problems with SCVs are pai-tly because of their large size and also

because the lllailufacturers are forced to oversize the engines to meet the perfoilnance

demands of the custon~ers. A l~ybrid SUV could meet the same perfo~nlance staildards but

\\auld be able to r ~ u i illore than a conventional vehicle on the same amouilt of fuel. HE

SU\-s ~\;ould be of great importance to the country's economy and could promote ecol~omic

stability in the event of a drastic cha~lge in fuel prices. The trade deficit could also be

drastically reduced in the long tell11 due to a reduction in the nation's dependence on foreign

oil.

DaimlerChrysler ailnouilced that it will star-t offering the Dodge Durango (shown 111

fig 2 .9 a. b 6L c) with a hybrid powel-train in 2003.

Fig 2.9 a

Fig 2.9 b Fig 2.9 c

Fig 2.9: Dodge Durango

The hybrid Durango con~b i~ ie s two separate propulsion systems: a 4.7 liter, \f 6

engine wit11 automatic transmission that poarers the rear wheels, and a three phase, AC

induction electric niotor that drives the front wheels The power ratings of tlie engine and

inotoi sere not available fi-om the source Tile electric lnotor assists the petrol engine during

3i~eleratio11. and recaphies energy llo~nially lost during deceleration. The hybrid

combination of poa,er sources provides the poner. acceleration and perfomiance of a

14

co i i~~en t~ona l V 8 englne. The hybrld power train yields a 20 percent increase 111 fuel

effic~ency; achieving 15.2 litres1100 kilometers combined citylhighway, compared w ~ t h 18.2

litresilo0 kilonleters for the conventional V8 Durango. [6]

Ford Prodigy (Fig 2.10), another hybrid electric vel~icle, uses a 1.2 liter compression

ignition, direct injection engiile called DIATA, which is lighter, and 35 percent more

efficient than convei~tiollal engines.

Fig 2.10 Ford Prodigy

The four cylinder DIATA generates 55 kilowatts, or 74 horsepo~ver, at 4,100 rpm. A

small, high power nicltel nletal hydride battery is used to generate the power for the vehicle

electronic systellls and call assist the engine as the vehicle accelerates and support the brakes

during deceleration, thus recharging the battery for later use. Battery voltages range up to

400 volts, with a peak current rating of 200 amps for 20 seconds and a continuous power

rating of 25 kilowatts. The motor ratings are not available from the source. [3]

1.1.4 Current Research and Development Efforts for Hybridization of Heavy \7el~icles

The hfassachusetts Bay Transpostation Authority in Boston has logged about 35,000

nliles on a pair of Olion VI buses powered by the HybriDrive(TM) system which uses an AC

induction motor to turn the vehicle's drive wheels. A diesel powered generator supplies

propulsion power to the electric n~o to r and to a battery pack. This configuration dramatically

reduces emissions while improving fuel ecolloilly by 25% to 50% and improviilg

performance over the convel~tional vehicle. The hybrid buses currently in service use diesel

engines, but the technology is compatible with other fiiel types, such as compl-essed nat~ual

gas and enlerging tecl~nologies including fbel cells.

The Allison Transn~ission Division of General Motors is planning to develop a series

hybrid electric transit bus which was on the market by October 2001. The New York City

Transit has developed series hybrid electric drivetrain propelled transit busses (Showil in Fig

2 .1 l ) , ~ v l ~ i c h traveled approxin~ately 300,000 miles in Manhattan.

Fig 2.11 A transit Bus

16

.A cornerstone of the NYC Transit Hybrid Bus program is the companq-'s Aliison

Electric Drives Thl hybrid system. At the request of the NYC Transit, Allison des iped a

series hybrid especially for the 40 foot RTS bus. The bus, which had already completed

about 70,000 miles of duty on Kew York City streets, was equipped with an .4llison Electric

Drives T'4 systen~ as part of a nolmally scheduled mid life powertrain overhaul. The urork

\&,as u13dertal;en in conj~inction with NovaBUS, the company that perfol-~ned the powertrain

integration

-4llison Electr~c Drives TL1 provide an improvenient in fuel economy of about 30

pa-cent over conventional heavy duty powel-trains. In addition, the systems offer excellent

en~ironmentrtl benefits for less cost t11a11 soiile alteixative h e l s that require complex and

costly fueling stations and other infi-astructure related expenditures.

NYC Transit's new hybrid bus features an Allisoil Transmission 160 kW traction

dri\.e sj-stem consisting of an inverter and drive unit. The diive unit includes a highly

integmted AC induction niotor and production gear reduction package. Additionally, three

bat121?. packs fl-0111 General Motors's S10 electric truck program p ro~ ides energy storage:

\f.l~ile a diesel hieled 100 kW auxiliary power unit from TDM, Detroit Diesel Coi-p. and

Uniq~lehlobility pro\.ides electricity to mail~tain battery charge. [4]

I-Tyhridization is also expected to help heavy trucks, especially long haul trucks: with

their fuel economy. Cul-sently the file1 economy of heavy trucks is very low and in need of

in-ipr~\~ement. Recent fig~lres fi-om the 21St Cent~1l-y Tnick Roadniap reference estimate that

tluc.1;~ are responsible for approxinlately 70% of the fuel consunlption in the nation. The

latest US govelvnlent sponsored vehicle research program, the 21'' Ceutul?; Truck Program,

, ,

is aillled at developing advanced technology that will enable safer, more fuel efficient and

more intelligent heavy duty vehicle transpo~-tation. Since this is a new initiative (announced

April 2000), no info~lnation is cun-ently available about hybrid heavy duty vehicles besides

transit busses.

In the following paragaphs infol-n~ation is given on collventional long haul heavy

duty vehicles to show the design issues and the need for in~provement of h e 1 economy. The

fuel econoruy of such collvelltional power train driven tn~cks when loaded up to 40,0001b

niay be less than 3 llliles per gallon of gasoline. This call be improved by the use of a hybrid

electric pon.er train which decouples the engine fi-om the peak power requiren~ents ihigh

torque is needed to accelerate such a huge vehicle from rest or to climb a slope) and allows

the engine to run nlost efficiently in cruisiilg range for which it could be designed the best.

The 2000 Sterllllg Backtruck (Fig 2.12) is a conventional h e a ~ y duty vehicle which

uses d colllpression ~ g l l ~ t e d dlesel eilgllle The big Sterling AT 9500 features a Cummlns N

\\1t11 500 11p and 1,850 ft lbs of torque available through its 18 speed Roadranger gearbox

The truck shon n belo\\ is based 111 Colac (Victona) and eanls ~ t s keep ca l lyng logs 111 from

the Om ay >lo~mtalns or Beaufort to Colac

Fig 2.12 Sterling AT 9500

1s

The 7001 Ken\\ortli SO0 (Fig 2 13) uses a 475kW Co~i ip re s s~o~ l Ignltlon ( C I ) eligille

The fionr axle has 120001b and the rear has 40,0001b capaclty The fuel economy changes a

lot \s.ith the load to be canied, but the figures are typically around 5 miles per gallon of

gasoline equivalent if canying around 8000kg of cargo. [ 5 ]

Fig 2.13 200 1 Kenworth SO0

3.2 Simulation Software and Studies using those Software

There are a lot of veliicular siniulation packages developed by different organizations to

prc.dict the perfo~-~nance: fuel economy and emissions for yet to be b~ii l t vehicles. They take

the input fi-om the user and give the output by virtually lunnin,o the vehicle through the

selecrzcl drive cycle.

Simplev is a DOS based Electric and Hybrid Vehicle simulation program developed

by the Idaho National Engineering and Environmental Laboratory. Its main use is as a

vehicle perfolnlance sin~ulation tool which capable of simulating vehicles having

con~.entional, all electric, series hybrid, and parallel hybrid propulsioil systems. The earlier

version of Sinlplev (Simplev 2.0) could not simulate parallel hybrid and conventional

i n t e~ l~a l conlbustion engine driven vehicles. Simplev is general enough to simulate vehicles

ranging in size fi-om sinall purpose built vehicles (such as golf carts) to fi-eight train

locomotives.

Slmplev allows the user to select a particular vehicle and its individual

coniponents like engine, batteries, transn~ission and n ~ o t o r and also a standard drive cycle. It

virrually runs the vehicle through the drive cycle and provides second by second predictiolls

of power train component perfollnance parameters over any user specified speed time or

speed distance driving regime.

SIMPLEV program was written by G.H. Cole. SIMPLEV Lvas prepared for the

L . S Department of Energy, Assistant Secretary for Conversion and Rene~vable Energy

(CE I. Under DOE Idaho Field Office, Contract DE AC07 941D 13223. [7]

To Order, contact:

Ms. Patricia Elickson Lockheed Idaho Technologies Company P.O. Box 1625 Idaho Falls, ID 8341 5 38 10 Phone: (208) 526 6854 Email: pze@inel.gov

2 0

Simplev simulation tool was used by Idaho national Engineering and Environmental

1,aboratory as a tool to calculate the acceleration perfo:oniiance and range for a widc spectrum

of clectl-ic vehicles ranging fi-on1 passenger cars and microvalis to full size vans wit11 a

payload of 500kg.

N E L has also conducted track and dynamometer testing of the Eaton Dual Shaft

Electric Propulsion (DSEP) minivan using Simplev. The Dynamometer data was analyzed to

detel-mine the energy consumpt io~~ of the vehicle for various dl-iving modes and to predict the

I - L I I I ~ C of the \.chicle.

CarSini

('arSini is a software package developed by AeroVironment, Inc. for simulating and

analyzing the behavior of four \vlieeled vehicles in response to steering, braking, and

acceleration inputs. CarSini includes a database that minimizes the time needed to build a

vehicle description and set up ruii conditions. Vehicles, components, inputs, existing runs are

acccssible with pull down menus in tlie database. CarSirn call only r-uodel series HEVs and

zlectl-ic vehicles, and is not capable of predicting enlissions. Cai-Sim is totally sclfcontained

and so i t requires no additional software.

To (11-dcr Contact:

Emnil: i i ~ f o @ ~ t r ~ t c l t s i ~ i ~ . c ~ i ~

H1:EC

Lawrence Livei-niore National Laboratoi-y has developed Hybrid Veliicle

Eval~~at ion Code (HVEC) that models tlie perfoiliia~ice and emissions of an all electric or a

series hybrid electric vehicle in response to a variety of operating conditions. Fuel cells may

be ~lsed in place of ICES as an auxiliary power unit, a flywheel limy be chosen as the energy

2 1

storage device instead of batteries, and a number of alternative fi~els (such as hydrogen and

compsessed natural gas) can be used instead of gasoline.

The physics il1cluded in the code is slmple d>rllamics. a ce~-tain amount of energ! is

requirc'd to per fo~nl a specified task. The model includes relationships between operating

coild~tlons and required perfolnlance data, such as \Jarlous energq losses in the system or

emissions. HVEC 1s one of a broad class of slrnulation codes that help des~gners cluichlq

analyze the perfo~lllance of a sqstem given a variety of competing designs 01 operating

conditions The results are then used to select the opt~lnal design, to focus on areas of needed

1niproT ement, to optlniize the operating cond~ t~ons , or to gain insight illto the dynam~cs of

tllc' s)htem [S]

To Order Contact:

Technical infoi11~at1on departiilent Lan rence Lil elmore National Laboratory [-nix ersity of Cal~fol-ma, Live~lnore. Callfolll~a 9455 1

CSA1 HE\-

The Colorado School of hlmes developed CShl HEV, a program dexeloped us~ng

;\IA4TLAB S~mul ink , xvhich allo\bs eas j configuration changes T h ~ s program also has tlie

capablllr) to do parametric sensltlv~ty studies through the ~nterface. Hornever, the

l ~ t s r a l ~ ~ r e ad~ui t s that the code \\.as still x ery 111uch under de\elopment and not ready to be

\alld,ttzd a~a111st actual nleas~lied data T h ~ s severel) l i m ~ t s the availab~llty of t h ~ s s~n~ula t lon

tool to a x4.ide ariety of users

1. Elph

V Elpli, an acronyil of Versatile Electrically Peaking Hybrid, is a

l~I.4TL..4B;'Simuli1ik based sirnulati011 prograln that was developed by Texas A&%f

University. \' Elph is much like CSM HE\- except with an improved user interface. \; Elph

facilitates in depth studies of electric vehicle (EV) and hybrid EV (HEV) configurations or

energy managemelit strategies through visual programming by creating components as

hierarcliical subsystems that call be used interchangeably as elnbedded systems. L' Elph is

conlposed o f detailed models of four major t p e s of components electnc motol-s. ~ntenlal

conlbustion engines, batteries: and suppo1-t compolients that can be integrated to model and

sil-uulate drive trains h a v i n ~ all electric: series hybrid, and parallel hybrid configurations. The

program was written in the hlatlabiSimulink graphical silllulatioil language and is pol-table to

most coniputer platfolmls. 191

To Order Contact:

Ziaur Rahman, Depart~~ieilt of Electrical Engineering Tesas A&hi Uni\ersity, College Station, Texas, Phone (409) 845 7441

;ID\-ISOR

.Ad\ anced 1-ehlcle Sllli~llator JA4DVISOR) 1s the most uidelq used and probabl:

the 111ost refined simulation program ava~lable today. This program uras developed b j the

Ncxt~onal Renev, able Energy Laborator) and 1s p r o s - m m e d ul th the use of

LIXTLAB SIL'lL'LIYK u l t h a kisual user ~ n t e r f ~ c e for easy man~pulation of colllponents

.4D171SOR 1s the pnmai-y d e s ~ g l tool used bq the Pal-tnersliip of New Generatlo11 of

\ ' e l ~ ~ c i e s ( P S G \ ~ ) It co~ltains the u lde range of features and broad flexib~llty necessai-y to

nlodel ally r y e of HEV or ICE vehicle, \x ~ t h a mlnlrnum of change ADVISOR can ut~lize a

\ane t> of custom and st311dard ~ T I V I I I ~ CYCICS. H o ~ SJ el-, u~lllke any of the other tools, ~t also

23

easily generates results fi-om batches of cycles, including the most recent draft SAE test

procedures for HEVs (SAE, 1997), with state of charge corrections and vehicle soak periods.

It can predict the fuel economy, emissions, acceleration, and grade sustainability of a given

vehicle and plot or data log ally number of intei-nlediate and final values. Another

pal-titularly conveilient feature unique to ADVISOR is the well refined graphical user

interface (GUI) which allows the user to easily select fi-om a list of custom or pre defined

base vehicles, intercl~angeable con~ponents, driving cycles, and outputs. ADVISOR can be

downloaded free fiom the website at nrel.gov. [ lo]

2.3 Related Research Work

Tesas ASLM has designed a series hybrid electric drivetrain for a heavy duty transit

bus using V ELPI-I. The simulation was carried out using Urban Dynamonleter Driving

Schedule (UDDS) and the results showed that the f~lel economy can be improved as much as

100% to meet the PNGV goals and the exhaust einissions can be cut down by the use of

Series Hybrid Electric poweltrain. The specificatioils of the n~otor and engine are not

available.

Tesas ASLM has also designed a parallel hybrid electric drivetrain for small passensel-

car. A small engine is used to supply power approximately equal to the average load power.

A vehicle controller and an engine controller manage the operation of the engine sucl~ that

the engine always operates with nearly fill1 load the optimal file1 economy operation. A11

induction ac illotor is used to supply the peaking power required by the peaking load

(electrically peaking).

24

Texas A b M has developed a11 electrically peaking hybrid (ELPH) electi-ic propulsion

systeill with a parallel configuratioii for a sniall car. A drive train for a full size five seat

passenger car has been designed and the results were verified using the V ELPH conlputer

siniulation package. The actual powertrain specifications were not available, but the results

suggest that a series hybrid electric car can easily satisfy tlie performance requiren~esit, and

the fuel econoiiiy can be ilnproved greatly over the conventional veliicles.

Texas ABthlI has developed a parallel hybrid electric drivetrain for a sinall car with an

engine power of 30kW aiid an electric nlotor of 42kW which is used for peak perforn~ance

~-equireme~lts and for recapturing the braking energy. The percent hybridization is aro~und

6Ooio. It was ~uentioned that the fuel economy was iliiproved but the actual figures were not

available from tlie paper. Ill]

University of Illiiiois at UI-bana Campaign has designed a series hybrid electiic dsive

train for a 1992 Ford Escort Wagon using Kawasaki FD 620D with a rated power of 17kW at

33001pii1, squirrel cage iiiductio~l motor rated at 15kW at 60hz (percent l~ybridizatioii of

around 50%) a generatioll of 2.2kW. 26 sealed lead acid batteries weighting 11.8kg each

were used as energy storage. The exliaust emissions are cut down reinarkably by the use of

this series liybrid. The fuel economy values are not ineiitioned in the results.

The University of .Alberta has designed a parallel hybrid electric dsive systeni for a

sniall car by using Suzuki, three cylinder, four stroke gas engine with 55hp (44kW) as the

in te~~ia l coii~bustion engine and a DC blushless niotor of 22kW as auxiliaiy power source,

(percent hybridizatioil of 33%) in conibinatioii with Niclcel Cadmium cells with a voltage of

170volts and 61Ali rating. Nickel Cadniiuni batteries have larger energy density (1.5) than

the conveiltional lead acid batteries, but are costly (272kg, 25,000 dollars). The vehicle had a

2 5

lange of 721tm on electrlc power and a total range of 500KM. The vehicle is capable of

meeting the PNGV goals of 80 miles per gallon ofgasol~ne with reduced emissions

Don Canipbell Is of LJnlvei-slty of Cal~fornla, Ii-vine has developed a parallel hybi~d

elcctnc d ~ i v e tialn for a Fold Escort wagon, w111ch operates 11-1 three modes, pure electl-~c,

h q b ~ ~ d and Z e ~ o Electrlc (ConventionL+l) He used a 3 phase AC induct~on m o t o ~ of 2 3 0 ~

with 3011p peak power and 6Oft Ib t o ~ q u e along with Geo Metro Lsi, Su7uk1 G 10 engine,

55hp, dnd 5Sft Ib torque For battelies, he used 26 cells of 12v lead acid battenes w ~ t h 20 Ah

rating The results indicate a fuel econoll~y of 50 illiles per gallon of gasoline

LJnivcrs~ty of Ca l~ fo l i~ l a has designed a parallel hybrid electric drivetram powered by

an et1i;lnol powered iiitcmal combust~on englne of 49hp and two AC induction motors o f

165x111 torque wliicli get poue r fio111 12 lead acid battenes.

The po~vtx ra t~ngs of the motors and the file1 econonly improvements were not mentioned

1121

Colorado State University has designed a parallel hybrid electric d i v e train for an

escort \\Tagon powel-ed by DC pemianent magnet 111otor of 34kW and a Kawasltlti internal

combustion engine of l6kW at 36001pm and a torque output of 47nm at 240Oi-pm. 'The file1

economy figures were not mentioned in the paper.

Dept. of Commerce and DOE conducted a mini s t~tdy to improve the f ~ ~ e l economy

of 3 ~011i.entionaI Spol-ts Utility Vehicle wit11 the use of Diesel Technology.

134kW SI engine of Ford Esplorer is replaced with a Compressio~l Ignited Diesel Engine of

12Sl;W to give the same perfollilance (0 60 mph in 9.5 sec) and the results showed hat the

fuel economJr for 3 CIDI engine is higher by 20%. [13]

26

Most of the research work done to date is currently on improvement of file1 economy

of small cars. SO, from tlie above hackground infornlation, this study concentrates on the

improvement of file1 e c o n o ~ i ~ y of Sports Utility Vehicles by the use of a parallel hybrid

electric drivetrain configuration.

2.3 Ilybridization Studies lisilig IIDVISOR

NREL has conducted a set of experiments to optiniize the file1 economy and

emissions for a small car propelled by 42kW engine and 32kW motor. The percent

hybridization (the ratio of motor polvcr to total power) is 321(42+32)*100= 40?4/;,. The

I-Iigh~vay I?uel Economy 'Test for tlie vehicle showed a fuel economy improvemcnt of over

209/".

The Automotive Research Center at the University of Michigan has co~lducted

simulations using ADVISOR software to predict the fuel economy of a Hybrid Electric

drivetrai~i propelled small car and concluded that the fuel econonly can be increased to meet

the PNGV goals of SO miles per gallon and emissions can be cut down to the extent of

n~ecting the Environmental Protectio~i Agency (EPA) regulations. [14]

L!ni\ ersity of Michigan, Ann Arbor has integrated a special prograin called TLII-bo

L)~zsel Engine Sinli~latioli (TDES) with ADVISOR to increase the accuracy of PI-edictions of'

file1 economy and p e r l b ~ l ~ ~ a n c e . TDES is a feed forward silliulation derived from the

f~~ndamenta l t11e1-n~odynamic equations and calculates engine properties at each crank angle

of a n illter~lal combustion engine. The results showed better predictions of the perforniance

~lnrl f ~ ~ e l economy because of the TDES. [I51

Chapter 3:

Iritroduction to Advisor

3.1 Introduction to ADVISOR

.4 sokvare tool called ADVISOR an acronym of ADvanced VehIcle SimulatOR is

used for this study . ADVISOR takes the input of the vehicle i.e., engine, transmission,

batteries, motor, etc along with their specifications f ro~n the user. It also takes the speed vs

time (drive cycle) to be traced by the vehicle from the user, then runs the simulation and

gives the results like fuel economy, emissions and time taken for acceleration. (For detailed

infornlation see Appendix)

3.3 Using ADVISOR

U11en you start ADL'ISOR, the first figure you will see is the startup figure shoun in the

Figure 3.1. Here you will have the options to select CTS or metric units, start using

'4DVISOR. click lzelp to go to a local ADVISOR web page, or exit ADVISOR.

The three basic steps involved in using ADVISOR are

1. Defining a Vehicle

2. Running a Sin~ulatioll

3. Looking at the results

3.2.1 Defining a ~ e h i c l e

Sturt talces ~ o u to the ~ n p u t figure The input figure (Flg 3 1 ) opens and you \ill1 see the

default balues fol a speclfic vehicle

Vehicle Config~iratioi~ Coillponelit Push Buttons and Pop up menu Sr Efficieilcy Map

E

Fig 3.1Vehicle Input Figure in ADVISOR

3.2.1.1 D r i ~ etrain selection

Flom the dribetraln popup menu you u l l l be able to select the dnve train collfiguiation of the

i _ I - -oai F 1- 1 ~AR-LLEL-detaiilt;-in - a,tlc-3 :r

Scnlo t81s- zeok -#a-5

D ~ t r elf fkai r Lahlrle / /l/ A/ 1 b ~ ~ ~ - ~ ~ ! ' . - i L J :

r Fuel ;?n\er,~i //m_ljjrlI/ / F C - C . I ~ ~ - r E~tiert;' . ~ n e t t r e s 1 / / - ~ ~ ~ I / [EZ-SI I

195 p-X 104

#3l norr ?! r E~EI:!, C I O ~ ~ ~ E /mJ/1)13 IESS-PB~~ - j :I,8 : - C

i J

r - r ~ n s i - i ~ ~ h l i ri j /,D~_Z] IT,-SSFIII 3 E l 1 4

r Torque ;oua l tn j //I)l/d r I I j J l j , \ j w - 5 1 . r t /

T13-@Uhll.(\, i

1] o r icreb;lr, , ~l~~~~ A X - H j BRID

r =qbber~ ra ~ c q t , t t 0 ~ ~ ~ T J l p ~ ~ : - p ~ 3 Cagc K '

C 4-

i override r n , r -

\ oriolsle Lid current ,

29

\.chicle (Series, Parallel, etc.) which will cause the schematic of the vehicle configuration in

the left pol-tion of the figure to change accordingly. This will also modify which components

are available for the tqpe of drive train chosen.

3.2.1.2 Selecting components

.qftsr selecting the drivetrain configuration, all the colllponents of the vehicle can be selected

i l s i n ~ the popup menus: or by clicliing on the con~pollent in the picture. To the left of the

component popi~p menus is a pusl~butron that \\.ill allow you to add or delete components by

selecting their coil-espondi~~g listed n~ files. The 111 file of a specific component can be

~~ccessed for \.ie\ving or nlodifying from eithex- the compoilent pushbutton or by clicking on

the component of the picture.

3.2.1.3. Editing F'ariables

Aftel- selecting all the desired conlponents for the vehicle, scalar input variables can be

modified. One n.ay this can be done is ivith the variable list at the bottom of the figure and

the Edit l"r. button. First select the variable to change and then click the edit button to

ch3ngz its \.slue. The default value is always s11on:n for your reference. The View All button

a1lou.s you to see all of the variables you have altered. You can click on the help button to

see 3 brief description and the ~ui~its used for the input variables.

-4 second Lvay in which you can edit variables is by typing in a desired value in the edit

boxes next to the component. For example, adjusting the maximuin power of a f~iel

converter adjusts the variable fc-trq-scale, or illcreasing the peak efficiency increases the

\.ariable fc-eff - scale accordingly.

3 0

A final way to edit the mass of the ve111cle 1s to use the override mass button. The calculsted

mass is ignored and the value input into the box is used instead

3.2.1 .-I J7ie\ving conipor~ent inform a t' ]on

At the bottom left pol-tlon of tlie figure there is a popup menu and axes w ~ t h the abi l~ty to

~nforrnat~on 011 componel-lts such as t11e11- efficiency maps, eni~ssions maps, file1 use

map" etc lThcsc are plotted along with their maximum torq~le envelopes where apl-71 op~atte

.An> compone~it m file call be viewed by clicking the comporlent buttons.

3.2 .2 Running a simulation

The simulation setup figure (Fig 3.3) glves you several options on how to test the

currently defined vehicle.

I/ Additional T e s t s I I 1 F i cce~e ia~ ion T e,t ACCBI O P ~ ~ O ~ S ]

r G,adeaocllh Test rnl Gmds 0pt8ans/

lime 1369 r

distance i 45 miles

marspeed 56 7 mph

avg speed 1 9 5 8 nlph

rnm scce' 4 84 h i s ^ ?

m i u decel -1 84 n15"2

a,,gaccrl 1 13Hlr"Z

uvq d e ~ e l -1 28 1 / 5 ^ 2

idle !#me 2 9 s no ol i,o0s

mar up grade 0 %

uvg up grade 0 %

m e dn qraue 0 %

3vg dn grade 0 >: L-.--

r Pararnctre Study 11-1 I

Fig 3.1 Simulatloii Set Up Figure in ADVISOR

3 1

3.2.2.1. Drive Cycle selection

IS the drive cycle radio buttoll 1s selected you call use the pull down menu to select fio111 a

list of a\ allable dllbing cycles

3.2.2.2 Accelel-ation Test

Bq select111g this chechbox, an acceleration test mi11 be 1x11 In a d d ~ t ~ o n to the chose cycle

Accelei-at1011 tlmes. maxlmunl accelerations. and distaliced trakeled m 5 seconds M 111 be

d~ \p l a>sd 111 the lesults figuie Thls test ~ 1 1 1 be run 111 addltlon to the selected d r ~ \ e cycle

'To see the secoild by second output of all acceleratlo~l test, choose the CYC-ACCEL fiolu

the cqcle menu

3.2.3 Looking at Results

The lesults figure (Fig 3 3) presents some suilliuary results and a l l o ~ s the user to plot up to

fbur tlllie series plots by selecting a \,anable from the popup menu.

If the acceleration and gradeability checkboxes n.ere picked in the simulation setup screen,

~ippl-opriate results will also be displayed.

By clicking the Energy Use Figure button. a neu figure is opened sho\\illg ho\\ enelg) fi a i

~ lsed dnd transfell-ed foi the \.eliicle durlilg the sin~ulation The Output Check Plots button

p~llls up plots that s11on the be l~~c le ' s perfo~illalice. some of w111ch are not apailable under the

time series plots

1 Results figure 1

1 Slm ~cttsl Teti ~ q t e l /

Fig 3.3 ADVISOR Results Figure

Chapter 4:

Powertrain Specifications

4.1 Scaling the vehicle components:

A vehicle is defined by selecting all the components required by the ADVISOR to

run a simulation. These components are to be selected from the available list for each

component type. For Example, ADVISOR users can choose fi-om seven different SI engines.

The SI engine so picked has a defined power rating, but ADVISOR allows the user to

overwrite the power in the vehicle input figure. The software then scales the engine to the

new power by altering the torque speed characteristics, mass and size of the engine

accordingly. The same is the case with the motor and batteries. It is assumed that the scaling

is done by the software is logical enough for the purpose of this study.

All the simulations in this paper use a manual transmission system only. The

o p t i n ~ u n ~ design may change when automatic or continuously variable transmission system is

used.

1.2 Engine, Motor Sr Battery Specifications

4.2.1 SUV SI Engine Specification

The base Intelnal con~bustion engine selected for the sports utility vehicle is Saturn

1.9L(95kW) SI engine .The power ratings of this engine are 95kW @ 6000rpm and a peak

torque of 165Nm @, 4800rpm as shown in the Fig4.1. The envelope of peak efficiency is

given in black lines with crosses, which means at those combinations of torque and speed,

the engine operates with its peak efficiency. The numbered parameter is the efficiency of the

encelope.

Fuel Converter Operat~on - Saturn 1.9L (95kW) DOHC SI Eng~ne 180 1 1 I 1 I

Fig 4.1 SI Engine Torque-Speed Characteristics

Higher or lower power from the SI engine is derived by editing the pourer vanable of

the aboi e SI engine. T11e power range used in this study is 40 to 200kW and it is assumed

that 111 this range, the software scales the engine effectively to a higher or lower polver levels

1.2.1, IIeavy Truch C1 Engine Specificatio~i

The IC engine selected for the heavy tlucks is 6.54L 8 cylinder naturally asp~l-ated DI

dlescl engine w ~ t h a maxlnlunl rated powel- of I 19kW at 32001pm and a peak torque of

400Nnl at 20001pm The power ratings of'this engine are 119kW @ 6OOOlpni and a peak

tori1~~eoo-f 400Nm @ 2 1001p1n as shown 111 the Frg 4.2.

I I I I I I 500 1000 1500 2000 2500 3000 3500

Speed (rpm)

Fig 4.2 CI Engine Torque-Speed Characteristics

Higher or lower power fi-om the 1C engine is obtained just by editing the power

variable in the advisor vehicle input figure. The power range used in this sti~dy is 40 400kIV

and 1s assumed that in this range, thc soflbvarc scales the engine effectively to a higher or

lower power levels.

4.2.3 AIotor Specification

The motol- used for a11 the cases is a Westinghouse, 75kW (continuous) AC i~lcluction

moto~;'inverter. The specificatiolls of the i~lotor are given in the Fig 4.3

Motortlnvertet ETTlcier~c~ and Continuous Torque Capablllb - Vqest~nghou;e 75-k'dv (contrn~~ous) AC lnduct~on rnotorl~nverter

300 /- I I I I

-300 I I I I

0 2000 4000 6000 8000 10000 Motor Speed (rpm)

Fig 3.3 Motor Torque Speed Characteristics

For 111gher or lowel power fi-om the motor, edltl~ig the power varlable in the advisor

\zh~clt : input figure scales the motor to the deslred power level

a Ions 1.2.3 Battery Specific t'

The battery selected for all the cases is Hawker Genesis 12v 26Ah sealed valve

regulated lead acid battery. See Fig 4.4

Exceptional deep discharge recovery a No col~osive gas generation

Long service life Quick chargeability Hlgh power density Maintenance free operation

1)imensions (in inches): 1-ength: 6.54 Width: 4.95 Ifeight: 6.89 It occupies 3.655 liters of space. The cost is $75

Fig 3.4 Pallasonic 12V128AHR Sealed Lead Acid battery4

A lead acld battery is made up of a series of identical cells each containing sets of

posltive and negative plates. Each positive plate is a cast metallic frame, which contains the

3 8

lead cl~oslde nctlve nlaterlal The negat~ve plates con ta~n spongy lead ac t~ve mater~al Both

platcs usually have the same surface areas.

The cell containing the plates is filled with an electrolyte made up of sulph~lric acid

and distilled water. Sulph~lric acid is a very active compound of hydrogen and sulphur and

osygcn a ton~s . S ~ ~ l p l i ~ ~ r i c acid is a very reactive substance and because of its instability it is

able to distribute itself very evenly thi-oughout the electrolyte in the bat te~y. Over time, this

action ensures that 311 even reaction can occur between all the plates producing voltage and

cun-ent. The chemical reaction between constitueilt parts of the electrolyte and tlie spongy

Icad of the negative plates and the lead dioxide at the positive plates turns the surface of botli

plates into lead sulpliate. As this process occurs the hydrogen within the acid reacts with the

oxygen within the lead dioxide to for111 water. The net result of all this reaction is that the

positive plate gives up electro~ls and tlie negative plate gains them in equal n u ~ ~ ~ b e r s , thereby

creating a potential difference between the two plates. The duration of the reactions

p~-nducil~g the cell voltage is linlited if there is no connection between the two plates and the

\,oltage will reniain constant.

If a co~ i i i ec t io~~ (a load) is placed between the positive and negative plates the

chemical reaction is able to continue with electrons flowing through tlie circuit from the

negative plate to the positive. The flow of electrons is in fact tlie current produced by the

cell.

Only when the supply of electlolls becomes depleted I e when the actlve rnaterlal

on the ncgatlLe plate has been used up, and the ions within tlie electrolyte have mostly beell

turned ~ n t o matel wlll the battely fa11 to p~oduce any current During the ;hemica1 piocess

3 9

different levels of heating can occur and the faster a battery 1s exhausted the greater wlll be

the heating and thus the efficiency of the system will be reduced.

4.2.5 The Problem of SOC (State of Charge)

A reasoilable rule of thumb is that you should aim to charge the batteries only when

they ai-e behveen 70% and 40% discharged. If you charge them then they are only lightly

discharged i.e. less than 4036 you will end up boiling them unnecessarily which Lvastes

enersy in the fol-ni of heat and gassed off hydrogen and in turn shortens the life of the

batteries. I11 effect the batteries are being overcharged which can cause degradation and

buckling of the plates. I11 the process some active nlaterial is forced off the plates and drops

down to the bottonl of the battery. If this occurs frequently the eventual result is a build up of

a bridse behveen the plates which in tu1-n can cause a possible short across the plates. This

situation leads to the destruction of a cell which then reduces the capacity of the battely.

As the battery charge capacity is not to fall below a certain limit, the sin~uiations in

this study are run n.it11 higher battery charge than usual for the vehicle platform. This

conser~ative design \$,ill allow the batteries to operate at higher SOC thereby and for higher

life 2nd higher efficiency, but the cost, space and \\.eight of the batteries is also coilsidered

and ~lccounted. [I61

40

The charactenstics of a single cell of thls batteiv pack at different temperatures 1s shoxn in

the Fig 4.5 and Fig 4.6. The three characteristics are coincident whlch means the effect of

tenlperature is negligible on the voltage and the power of this particular battery module

I I I I I

0 0 2 0 4 0 6 0 8 1 State of Charge, (0-1)

Fig 4.5 Battery Open Circuit Voltage Characteristics

Fig 4.6 Battei-y Instantaneous Power vs SOC

The ~li~l l lber of lllodules of the batteries 1s scaled according to the amount of energ)

to be \toled Inc~cdsing the numbel of cells of the batteries increases the peak Loltage and

pow el piopoitlonally at the same atnpele hour rating of the batte1-j ADVISOR scales the

mass of the batteries pi-opo~-tionally.

Chapter 5:

Design Methodology

5.1 Overall goal of the study

The goal of this study is to arrive at an "optimum" percent hybridization, which

trades off file1 economy and perfomla~lce of the selected vehicle. This is done as two

different studies, one with, and the other without cost consideration, and is also done for

three vehicle platfomnls, light SUV, fill1 size SUV and Heavy Trucks.

One of the three vehicle platfol-nls IS selected and a reasonable power level for that

vehicle platfornl is taken from the data of the current conventional vehicle type. The vehicle

is then hybridized by replacing (in steps) this power by an equivalent motor power and a

simulation is run. Such simulations are iun in ADVISOR at three different battery charge

capacities to under stand the effect of on board charge. The fuel economy and the time to

accelerate from rest to 60 n ~ p h are noted down from the ADVISOR results.

5.2 Design Technique Employed

5.2.1 Technical Optimization

The optimum percent hybridization for fuel economy and perfomlance is calculated

in the following manner. Fuel economy is given 30% weighting factor and the performance

70'!/b. Performance is assumed as the inverse of acceleration time. (The assumption made

here is, the quicker the vehicle, the better is the performance) The performance is given a

higher factor in this design to ensure that the hybrid vehicle does not fall behind by too much

111 performance, which is the key for marketing. The fuel economy and the performance of a

conventional vehicle are taken as unity and r'or the calculation of the optimum, the mileage

or performance at any power split is taken relative to the conventional.

The follo\ving is the formula used for the calculation of the weighted combination of fuel

economy and performance. Let us call this as Net value (Equation 1)

Fuel Econornv at n particular percent hyhridizntiori Net Value = 0.3*

Ft~el Econom,v of the convcntionnl with the sar~ze power

Perfonnnnce at n partictll~zr percent hybridization + 0.7* ...( Eqn 1) Peufo~n~aizce of t11c conventional with the same power

Even though these weighting factors are used, the posslble effect of other weighting

filctors on the dcsign will also be exarniiled in the analysis. The corresponding Matlab codes

for a11 the vehicle platfornls are in Appendix 2.

5.2.2 Cost Based Optimization

The cost of the vehicle is also considered in this study. The cost optimization is done

by considering the cost of the motor along with the cost and space of the batteries. The

benefits due to the decrease of operating costs will be shown in the fuel economy and the

paialty due to the weight of the batteries is shown both in performance and fuel economy of

the vehicle.

It is assumed that the cost of the base IC engine remains constant and the cost

penalty is due to the batteries and motor. The cost o f a battery is taken as $75 per single cell

of 12v. The cost of the motor is considered to be $15 per Kilowatt of power in addition to a

fixed cost of $200. For example, the cost of 40 kW nlotor will be $ 200 + $ 15 * 40 = 5 800.

The values of the cost of the motor are obtained from the price list available on the Internet.

1171.

The replacement cost of the batteries is not considered because the replacement cost of

the batteries in a hybrid is taken equal to the replacement cost of tlie IC engine for a

coii\~eiitional vehicle. The excess cost due to the batteries and motor is considered as cost

penalty and is added to the vehicle cost for the cost optimization.

For the cost optimization, the following data is taken from Evworld.con~. A lifetime

of 14 years is assumed for all tlie vehicles and is estimated that each vehicle travels 12,000

niiles per year at the gasoline cost of S 1.40 per gallon. The cost of the conventional sports

utility ehicle and that of heavy tl-~lck are assumed to be S20,000.

Cost S a ~ ~ i n g s in Vehicle lifetime of 14 years (,411 parameters for 14 years) =

Fuel cost savings- battery purchase cost- motor cost

Fuel cost = [GPM for the vehicle - GPM of the conventional]" No of miles traveled "Cost of

gasoline in dollars per mile

Mhere GP,M is the gallolls of gasoline required for traveling one mile, the reciprocal of f ~ ~ e l

economy. The cost of the conventional SUV is taken as $25,000 and that of a heavy truck is

taken as $30,000. The Net Value is calculated as shown in Equation 2

Net I 'alue (with cost consideration) =

Cost of tlze corive~ztioizcrl velzicle 0.15"

Cost of tlze vehicle at u par-tzcz~lclr percerzt hybr~iclizatioi~

Pelfon~zai~ce at n pai.ticulnr per~eizt 1zj~br~idi:ntion - 0.45 "

Per.fbrrnaizce of the corzverztiorzal with the snine power

Free space available ill tlze pnirticzllar HE V -0.1 * . . .... .. . .... .. ..... ..... ... . .(Eqn 2)

Free space zrz the converztiolzal vehicle

The cost and the perfollnance are given lligher weight because they are key factors to

niarltet a vehicle. The batteries occupy some space, which will decrease the free cargo space

in the hybrid vehicle. This is also considered as shown in the equation. The above eq~~atiol l

gives the net value of the conventional vehicle as unity and the remaining vehicles can be

taken relative to that vehicle The additional cost due to the batteries and the motor is taken

relative to the conventional vehicle of that type and the fi-ee space available is taken relative

to the approxilnate fi-ee space available in the conventional vehicle of that type.

Even though these weighting Gctors are used, the effect of the change of weighting

factors is also exanlined whether it makes any difference on the optimum design.

Chapter 6:

Simulation, Results and Conclusions

6.1 Control Strategy Employed

All the simulations are run using a parallel hybrid electric control strategy (See

Appendix) in ADVISOR. The motor can be used in the following ways.

1. The motor can be used for all driving torque below a certain minimum vehicle

speed.

2. The motor is used for torque assist if the required torque is greater than the

maximum producible by the engine at the engine's operating speed.

3. The motor charges the batteries by regenerative braking.

4. When the engine would run inefficiently at the required engine torque at a given

speed, the engine will shut off and the motor will produce the required torque.

5. When the battery SOC is low, the engine will provide excess torque, which will

be used by the motor to charge the batte~y.

6.2 Simulation and Results for average SUV

A 150kW total power is selected for an average sports utility vehicle and is

hybridized (in steps) with a motor at three different batte~y charge capacities for each power

split. In the following case, the number of lead acid cells selected is 25,35 and 50. Fifty cells

of 12v at 26Ah may be too many for a compact SUV based on the space constraints, but the

idea of selection of higher batte~y cells is that it will help the batteries operate at a higher

SOC, which will improve the efficiency of recharging and life. However, as the cost

increases with higher number of ceIls, the cost optimization takes into account the space,

weight and purchase cost.

The drive cycle selected for the simulation is Federal Test Procedure Drive cycle (See

Fig 6.1) that is the cycle reconlnlended by the United States Environmental Protection

Agency for the emissions certification of the passenger vehicles in United States. The drive

cycle sinlulates city driving and has idling and good acceleration requirements.

CYC-FTP 100 - I

speed elevation

f" Oescrrptron F Statistics

0 50 100 Speed (mph)

time: 2477 s

distance: 11.04 miles

max speed: 56.7 mph

avg speed:

rnax accel:

max decel:

avg accel:

avg decel.

idle time:

no. of stops.

max up grade:

avg up grade:

max dn grade:

aLJg dn grade.

16.04 mph

4.84 ft/sA2

-4.84 ft/sA2

1.1 4 ft/s-2

-1.27 ft/se2

359 s

2 2 0 %

0 %

0 %

0 %

Fig 6.1 Federal Test Procedure (FTP) Drive Cycle

48

The percent hybridizations selected for this study are obtained fi-om calculation of

percent nlotor power out of the total power, which always remains constant at 15OkW. The

coi-sesponding data is tabulated in Table 6.1.

Table 6.1 Results fi-om ADVISOR for a 150kW powered average SUV

The motor power is initially zero, which means the percent hybridization is zero.

Vvl~en the noto or power is 100kW, the percent lzybridization will be 1001150, which is 66.7%

and so on.

The plot between fuel economy and percent hybridization (Fig 6.2) is obtained by

ta1;ing into consideration three batteiy module levels at each of the seven different percent

hybridizations selected.

P Battely Modules Percent

Hybridization

25 Battely Modules 50 Battely Modules

Miles per

Gallon

Miles Per

gallon

35 Batte~y Modules

Acceleratioll Tinle

(0 60 mph)

.4cceleration time

(0 601npl.1)

Miles per

Gallon

Acceleration time

(0 6Omph)

# Modules

15 - -- - - -. .-

0 10 20 30 40 50 60 7 0 80 90 Percent Hvbrid~zat~on

Fig 6.2 Fuel Econonly (mpg) vs. percent hybridization for an average S I J T

The lines in this plot and all si~llilar plots in this report do not represent a

relstiousl~ip betn eel1 the parameters. they are included merely as a convenience to 11nk the

data points for a conlmon lumber of battery modules. 111 other words, no relation is implled

beyol~d the values at the individual analysis points

The acceleratio~i test is conducted at the ba t t e~y state of charge of 0.65 and the

parallel hybrid electric drive co~ltrol strategy ~ n i n i r n u n ~ SOC limit is 0.40 i.e., only 5% of the

total battery charge is used for the test. The limit for SOC is set at 0.45, which is closer to the

5 0

minimum SOC (0.60) because, in the seal world, the vehicle may need to accelerate several

tinles in its drive, when the battery state of charge is not necessarily high. For this reason,

sq'stei~~s with large percentage hybridizations are at great disadvantage since they have very

little energy available for acceleration. This result is shown clearly in Figure 6.3. In other

m,ords, veliicles that depend heavily on electric power for their propulsion use up a lot of the

battery charge and get illto lower SOC sooner and reduce the efficiency o f the battery. The

vehicles that are less hybridized have big enough engines and they depend lesser on the

batteries and hence the batteries will be at a good state of charge for most of the tirile and the

operation u d l be efficient.

Percent Hvhridizatinn

Fig 6.3 Acceleration time (0 6Ompl1) vs. percent hybridization @ different charge capacities of the batteries for an average S W

J J T h e ~ ~ both the fuel econonly and acceleration time are considered and lve~ghed

according to the equation 1 , the net value can be calculated and plotted against percent

hqbnd~zation as shonn 111 the F~gure 6.4

Fig 6.3 Net Value (Combined Fuel Economy and Perfonllance) vs. percent 11yb1-idization for an average SUV.

The net value is maxinlized at around 30 percent hybridization and the peak shifts

to\\,al-ds higher hybridization with the increase in onboard charge. It can also be noted that

n.il11 the increase in the total onboard charge, the net \ d u e increases showing that Inore the

charge you could afford to caily onboard, the better is the net value.

5 2

The Effect of Purchase Cost of tile Vehicle:

The cost of the vehicle is calculated as the cost of the conventional engine plus the

cost of the motor and batteries. Fig 6 . 5 gives the cost of the vehicle at different percent

l~ybridizations and wit11 different battery charge capacities (Vumber of battery modules)

Percent H'jDr ici~zatioti

Fig 6 . 5 Cost of A\.erage SLV vs. percent hybridization

It can be noted that the cost o f the veh~cle shoots up with the int~oductlon of the

11mtoi and bilttelies and later the cost glows slowly u l th the increase of motor power This is

because the cost of the motor 1s considered as the base prlce plus the cost for addlt~onal

pow er d e i ~ ~ e d Also, it can be clearly noted that the cost of the vehicle Increases u ~ t h the

5 3

increase in on board charge It can be noted that the effect of batteries on the cost of the

1 elllcle 1s Illore significant than the effect of llzotor.

Cost Optilllizatroll rncludes the cost of the \ehlcle, perfo~nlance and space occupancy

ielatii e to the con\ent~onal kehlcle Fol a cornpact SUC' wlth 15 battery nlodules of on board

chalge. the con-espondlng ratlos are plotted For e g., Cost Ratio lndlcates tlie ratio of the

cost of the 1 ehicle to that of the con\ entronal vehlcle of that type It should be noted that the

cost ~ncludes not only the purchase cost, but also the file1

savings in the long 1-uii.

It can be noted from the Fig 6.6 that the cost of the vehicle increases with the

increase in percent hybridization, even though it includes the cost savings associated ~vith the

use of hybrid vehicle. This nleans that tlie cost savings cannot more than offset the increase

in purcliase cost.

F I ~ 6.6 Colllponents of Cost Optilllizat~o~l for aTerage S W with 25 battery niodules

5 4

The weighted conlbination of the cost ratio, perfo~mance ratio and the space ratio

produce the net value which is slightly lower than that of the conventional vehicle for nlost

of the percent hybridizations. It has to be noted thdt the research towards the manufacture of

low cost batteries should f~u-ther improve the cost ratio of the hybnd vehicle The net value

nl th cost o p t i n ~ ~ z a t ~ o n is glven m the Fig 6 7

Fig . 6 7 Net Value ~vlt11 Cost C'onslderat~on vs percent hybridization

Wllen the cost is also cons~dered, 11 can be noted that the net value of a hybnd

e l rc t i~c ehlcle comes down w1t11 the 111ci-ease In the number of battery n~odules as opposed

13

1

0 98

12 96 - - , I - IT,

093- E - \x - 0 - n 92 - ffl 5 i-) - 09- II' 2 - n >.

Fercerit Hybridization

.. I I I I I I I I , \

.,, ---1 ~~ 1. # Molclules

- --- %., \ 1..

- i -X - \-.. El --

\r. , - .-. v '. x..

..,-.- x, - -i. '.,

-.. . \\. - . . -

- . , ~.~>\:\, \ *

\-, \ .,~.,'+, 3%). -

'\\ ?A - [I $3 ..:\ i

3 -7

0 8t3

0 84

0 $2

-

'*,.,.., *-,*

- '%:%.. .. >. -

'\,', , I

\ '.. - l. \, ?> -

\, '\

I I I I I I I I + i3 10 20 3 0 40 5 0 6 0 70 80 9

5 5

to the earlier figure (Figure 6.4) whel-e cost is not considered. The comparative plot 1s shown

In the Fig. 6.8.

Percent HyGr~dizat~on

Fig 6.8. Comparison of Technical and Cost Optimizations for average SUV with 25 battery modules.

T h ~ s represents the cost of the batteries rZlso the curve has a bottom, but not a peak,

uhlch ~ndicates that %hen the cost 1s givcn a very 111g11 slgnlficance (350/;,), the value of the

11) b~ id electric cehicle runs further down compared to the convent~onal vehlcle

The effect of illdividual components on the net value are show11 in the Fig 6.9

I I I I I I I I 1 0 - - 10 L u 3 13 40 5 0 60 70 80 90

Percent Hybi'ld~zation

Fig 6.9 Conlpollellts of Cost Optii~lization for average S W with 35 battery modules and with low cost batteries.

With the in~provenlellt in the battery technology, let us assume that the batteries last

longer for about 14 years, so that there will be no replacement cost of the batteries, the net

\ialue fbr the hybrid electric vehicle would be greater than that of the collvelltional vehicle

with peak at 20 percent hybridization as shown in the fig. 6.10.

Percent Hybridizatlon

Fig 6.10 The Effect of Low Cost Batteries for an average S U V

The Fig 6.10 indicates the effect of possibie low cost batteries that could be possible

in the near f~lture lvith the oilgoing research on fuel cell batteries. This may increase the net

\value of the vehicle by about 10%.

5 8

Let us examine the changes in the optimum percent hybridization and net value for

the changes ill the weighting factors. The weighting factors are taken with a file1 econon~yl

perfonuance combination ~-allging from 15/85 to 45/55. It can be observed from Fig 6.1 1 (a)

that the technical opti~~lurn goes in line with the increasing fuel econoniy which means that

n~ore the impoi-tance given to file1 economy, the more is the net value we could realize. It

should also be noted that the peal< does not shift to either side which implies that within the

gi\,en precision points (only for every 20 percent hybridizatio~~, data is analyzed) the peak

does not shift because the opposite trends of fuel economy and perfornlance. The same trend

could be observed in the case of other vehicle platfornls too.

Fig 6.1 1 (a) Technical Net Value Change xvith the variation of Weight~ng Factors

1 2 - . . . ___j_

/ < , ,,' \, '- .,,, - . .. .- i'..

/,, ,/" . 'q . ~. . ..

i 5' . . ,. '..,

T i l - / . i *, .. - .. - .('>? C ./. ., '.\., -. 7 - =i'

. . .. .- . ' \

I.._

2 */ * '.. '. _ - i I - IL' - '.~ - l! = ... > -\. . - p 0s-

*

0 7

0 6

.\ '.. %. .

*.. ' ..c L*. . --

\\.. - - .. Weighing Factors (%) .--

l,.., 't,

- Fuel Economyi Performance - ,

+ 15/85 \

ir 25/75 -* \ - '-,

35165 '- ._

-+ 45155

- 1 I I I I I

0 10 20 30 40 50 60 70 90 '3 0 Palcent Hybridzaton

Similarly in the case of cost optimization, slight variation of the weighting factors

affect the cost optimized net value of the vehicle a little bit by shifting the peak up with the

decreased weight age of the perforillance Fig 6.1 1 (b).

Fig 6.11 (b) Cost Optimized Ket Value Change m ~ t h the variation of Weighting Factors

k _/--a\.. ,] <... ... .": '-. -

1 -:? :..\. .. -. \,... '..

But the optinluill design still renlains the same (the location of the peak). This means

-. ;=? i]"- dtr $ - E - - 0 0.9- - LO 0 C7 -- a, CI 85 - J - m --. /- - a) z 08-

if the customers give illore ililportance to costs, the hybrid vehicle suffers in its net value as

'.. -.-..\ -. - --..- ..--. %\, -., ,.-, '' . :-- . ., --,y:,. ,.

\.\., -.-..- .., $.+---- . . - -, +\$\

-.. -.\ -- ---- ;'>"..h -_ .-. ' - .-+& - X--__ +a\

Z '<:,>-- << .; -\

1 ---+ -

'q<. ., --&-

y;-,. - < . , 1 --%)

- -

L'i'e~gi-ling Factors ( C;'n) Cost' FeiformaricelSpace -

shon n 111 the graph.

-3- ?5/65/1Ci \\

7 +-- 35/55/10

+ 55,'351'10 i;- 65\25/10

r3 T I I I I I I I I

0 10 2 Ci %. 413 50 6 0 7 Ci 8 0 9 i3 '2, p

Percent 'iqbr-~dization

6 0

6.3 Simulation Sr Results for Full Size SUV

A total power of 200 KW is selected for a full size sports utility vehicle and the total

power is gradually hybridized using an induction motor and a battery. It is assumed that

adding 500kg of cargo and 10% increase of frontal area to the compact SUV scales the

vehicle to a full size sports utility vehicle. As the fill1 size S W has much frontal area and

slightly heavier mass than a coinpact SUV, it is assumed that the above scaling is reasonable.

The number of battery nlodules tested is 25,50 and 100. Fifty or hundred cells of

1 2 ~ at 26Ah may be high for a f ~ d l size SUV, but the idea of selection of more batteiy cells

is that it will help the batteries operate at a higher SOC, which will improve the efficiency of

recliarging and life. However, as the cost increases with higher number of cells, the cost

optimization takes into account the space, weight and purchase cost. The results are

tabulated in Table 6.2 and are plotted in Fig 6.12 and 6.13

Table 6.2 Results from ADVISOR for a 200kNT powered full size SUV

* Battery r\.lodules Percent

Hybridization

0 2 0 3 0 3 0

i 5 0 6 0

I 80

25 Batteiy Modules

Miles per

Gallon (n1pg) 13.6 18.6 19.6 20.8 22.0 23.3 28.8

Acceleration Time

(0 60 mph)

8.8 8.4 8.9 9.6 10.5 11.8 16.3

SOBattery Modules

Miles per

Gallon (n1pg) 13.6 18.6 19.6 20.8 22.1 23.5 30.1

100Battei-y Modules

Acceleration time

(0 6Omph)

8.8 8.1 8.2 8.6 9.4 10.4 12.4

Miles per

gallon (mpg) 13.6 17.9 19.0 20.1 21.2 22.7 29.8

Acceleration time

(0 60mph)

8.8 8.9 8.3 7.8 7.5 7.7 8.4

Fig 6.12 Fuel Economy (mpg) 1,s. percent hybridization for full size S U V

Fig 6.13 Acceleratioil time 1,s. percent hybridization for fill1 size SLV

17

16

- g E 15-

1 4 - 0 + 0

E 1 3 - 0,

# Mod~les - 7C

El/''- -

/ //'

- ,I2 - ,/ , - j E -

/, / '

/A' .,25

-

0 10 20 30 40 50 60 70 80 Percent Hybrid~zaiion

6 2

It call be noted Fig 6.12 and Fig 6.13 that the fuel economy and the rime to

accelerate from rest to 60mph show similar trends as of an average SUV.

Simiiar to that of the average SUV, it can be noted from Fig 6.14 that the net

technical value increases with the increase in battery modules. This means the availability of

additional electric power increases the perfo~lnance of the vehicle predonliilantly

'IS,

08' I

I 1 I I I I I

0 '1 0 2 0 3 0 40 5 0 60 TO 80 Percent Hybridlzat~on

Fig 6.14 Ket Value (Technical) 1 s percent hybridization for f~ i l l size SLY

63

Similar to those with average SUV, cost of the vehicle, the cost ratio, space ratio and

the perfom~a~lce ratio exhibited the same trends as shown in Fig 6.15 and Fig 6.16.

Fig 6.15 Cost of full size SUV vs, percent hybridization for f~111 size SbV.

0 10 2 0 3 0 40 5 0 6 0 70 8 0 Percent Hybrldlzatron

Fig 6 16 Components of Cost Opt~mization for full size SUV with 25 modules

6 5

The trend In the net value for the full size SLV as a function of percent 11?bi-~d~zatloil

~ 1 1 d ~ ~ u ~ n b e i - of battery modules 1s shomn 111 Fig 6.17.

Percent Flybridization

Fig 6.17 Xet Value (Cost Optiruization) vs. percent hybridization for Full size SUV

The low cost battei-y technolog? could improve the net value of the vehicle o\er that

of the conventional vehicle. The peak of the net value could be observed at about 30 percent

hybridization as shown in the Fig 6.18

Fig 6.18 Co~ilpo~lents of Cost Optilnization for full size S U V with 25 modules

6.4 Simulation S: Results for Heavy Trucks

A total power of 4001tW is selected for simulation of a heavy tluck and is loaded

wit11 3 cargo of 8000kg. T11e total power is gradually hybridized with a niotor at three

different battery charge capacities for each percent hybridization.

In the following case, the nulllber of nlodules selected is 50, 100 and 150. Higher

nulliber of batte~y cells may cause practical problems like space and weight, but will help the

batteries operate at higher SOC which is good for the life and efficiency of the batteries. But

the space, weight and cost are all penalized in cost optimization.

The drive cycle used for the simulation of heavy trucks is Inter state Driving

Schedule. (Fig 6.19) Mostly, heavy trucks are s ~ ~ p p o s e d to carry load from state to state. The

above drive cycle simulates the inter state driving co~lditions as it travels partly in city and

mostly 011 the highway. The ADVISOR results for heavy truck are tabulated in Table 6.3 and

the file1 econoniy and acceleratio~l time are plotted in Fig 6.20 and 6.21 respectively

CYC-WVUIIdTEF? bO

key on speed

60 - -- elevatlori -- r 2,

3 9 ,-.-

f -- K. - U

- 8-i 1,

'1) - -

iU c ?Z u- '2: -

;y?

2 0 --!I 5

o=J- v _ '?

0 500 1000 1500 2000 time (sec)

SpeediEIevation vs Time y

"

0 5 0 100 Speed (rnph)

time

distance:

mau speed

avg speed

maw accel:

maw decel

avg accel.

avg decel

idle time.

no of stops.

maw up grade

avg up grade.

m a y dn grade.

avg dn grade

1640s 1 5 51 miles

60 73 mph 34.04 mph 4 67 R/s"2

-6 09 his-2

0 44 ft/sA2

-0 47 t t isA2

1 5 2 s 9 0 %

0 %

0 %

0 %

Table 6.3 Results fi-om the ADVISOR for a 400 kW powered Heavy Truck

Fig 6.20 Fuel Econon~y (111pg) VS. percent hybridization for heavy trucks

F Battery Modules Percent

Hybrid~zatioi~

50 Battery Modules

Fuel Economy

(mpg)

Acceleration Time

(0 60 mph)

10OBattery Modules

Miles

Per Gallon

150 Battery Modules

Acceleration time

(0 60mph)

Miles

Per gallon

Accelen-ation time

(0 60mph)

Table 6.3 Results from the ADVISOR for a 400 kW powered Heavy Truck

Fig 6.20 Fuel Econonly (mpg) vs. percent hybridization for heavy tiucks

# Battery Modules Percent

Hybridizatiotl

50 Battery Modules

Fuel Economy

(mpg)

Acceleration Time

(0 60 mph)

1 OOBattery Modules 150 Battery Modules

Miles Per

Gallon

Miles

Per gallon

Acceleration time

(0 60mph)

Acceleration time

(0 60mph)

I I I I I I

0 I ir 20 30 40 50 SO 70 8 0 Percent Hybrldlzation

Fig 6.21 Acceleratio~i time (0-60111pll) vs. percent hybridization for heavy trucks

Just as in the case with other vehicle platfonils, it can be noted from Fig 6.22 tliat the

peal; of the net \ d u e sliiftzd toward the higl~er percent hybridizations with the il:crease in

b~itler>, charge capacity. It call also be noted that in heavy trucks the peak is around 1.6,

\vhizli is much higher than tliat for the SbVs . This is due to the fact that in case of hea\.y

tl-~iclis. the acceleration needs (even though significantly lower than S W s in regard to time)

req~lire higher power engines to accelerate sucli a heavy mass. So, the engines are typically

o\,ersized and hj,bi-idizing these vehicles llas a huge impact in fuel economy and

acceleration.

I I I I I

A+ Modules

Fig 6.22 Net Value (Technical Optimization) vs. percent hybridization for heav). trucks

Trends silllilar to those in other platfonlls can be observed in the purchase cost, cost

ratio, pertbulllance ratio and space ratio as shown in Fig 6.23 and Fig 6.24.

F I ~ 6.23 Cost of heavy truck vs. percent hybridization.

Fig 6 .21 Colllpo~leilts of Cost Optinlization for heaty truck

[; 5 !-

0 1

! --+ C D S ~ Eatlo

0 " . I I ) I I

0 I0 20 3 0 4 0 5 0 6 0 70 8 0 Percent Hyijr~d~zation

O 4 - Paforrnance Ratio - space i la to + Net 'dalue

72

With 50 battery modules and 25% hybridization, the net value of the vehicle call be

increased to 1.4 tiines its original. This effect is also sipificantly higher than that in the

SlJVs. It call be clearly seen from the Fig 6.25 that the additional battery modules over 50

tend to reduce the net value, since they are espensive.

Percent HyGr~d~zat~or~

Flg 6 25 Ket Value (Cost Optimizat~on) \.s. percent hybridization for heavy 11-ucks

So, hybrid electric vehicle is unable to take advantage of the additional power

beca~lse of its higher cost. But in fi~ture, if the batteries were produced at low cost using fuel

cells. then the pe r fo~~nance and fuel e c o n o ~ ~ l y irnprovellleilt that can be realized technically

(3s ill the case of technical optimization in the Fig. 6.22) would become practically feasible.

The coinponents of cost optimization with low cost batteries are shown in the figure

6.26 where the net value is increased over that of the conventional vehicle. The effect of low

cost batteries is also represented in the Fig 6.27 as a con~parison to the net value with

original cost of batteries.

Fig 6.26 Components of Cost Optimization for heavy tnlck with low cost batteries.

Percent Hybridization

Fig 6.27 Effect of low cost batteries on the net value of heavy truck

It call be obselved that with the advent of low cost batteries, tlie percentage increase

in the net value is more for the heavy truclis (20%) than for SLVs ( 5 to 10Y0). This is a clear

indicatiori that tlie researcli in the directioli of improvement of battery technology could

mal<e hybridization riiore feasible to heavy vehicles.

-7 - 13

6.5 Conclusion

The con\ entlonal englne that IS sued for ~ t s peak power requ~rements has a poor

fuel economy But as we l~ybndlze the total power, I e , w ~ t h greater power denbed fiom the

motor. the iilel economy Illcreases because the IC engine 1s allowed to be downsized and be

operated in a more file1 efficient zone. Here, the increase in fuel economy is automatically

accompanied with the decrease in e~nissions due to the fuel efficient engine. Since lesser is

the f ~ ~ e l bunlt. the lesser are the emissions. The steep rise in tlie fuel economy at fu~tlier

h\.bridization is deceptive because there the total power is derived from tlie batteries and

iiiotor and the base IC e~lgine supplies very less power. This means that the vehicle is

ruiining almost electric, a i d we need to cal1-y sufficiently large amount of onboasd charge for

longer distances.

The time to accelerate fi-om rest to 60 mph comes d o l ~ n with lower percent

hybridization for all the vehicle platfol-nls. This is because the vehicle needs higher in~tial

torques for better acceleratioll and the use of a nlotor which is capable of generating higher

torques at lo\ver speeds (compared to the IC engine) helps the vehicle accelerate faster. But,

ii~rrher hg.bridizing, i.e., dowllsizing the engine and deriving more and more po\ver from the

motor depletes the charge off the batteries quickly: tl~ereby decreasing the state of charge

(SOC? defined as a ratio of existing charge to the full charge capacity) and the charge

replenisliment of the batteries proves costly at lower SOC, i.e., to replenish a certain amouilt

of lost charge of the batteries at lower charge capacities, more power is to be used than to

replenish the same amount of charge at higher SOC. So, there is a minimum SOC limit

below which it is not advisable to operate the batteries. This puts a limit on going for high

power motor by downsizing the base IC engine. If we want to go for further hybridization:

the ba t t e~y charge should be increased and we can derive more power from the batteries for

acceleration and grading pulposes at higher SOC. This can be observed that the point of the

best acceleration moves towards greater hybridization percentages with increase of on board

charge of the batteries. So, more the charge we cany with the vehicle, the better will be the

acceleration.

Technical optimization considers 'Net value' which takes into consideration both the

acceleration and fuel economy. In all the three vehicle platforms, the peak of the net value

curve increases with the increase of on board charge. This means that if we have more on

board charge, the overall perfornla~lce will be better. Moreover, the peak shifts towards

higher percent hybridizations with the higher battely charge capacities employed. This

nlenns that with more on board charge, it illakes sense to use a better motor.

The cost optin~ization takes into consideration the space constraint of the batteries

and the total cost of the vehicle while calculating the 'Net value'. The increase in total cost

fsom the conventional vehicle of the same type is due to the cost of the batteries and motor.

The Net value in the cost optimization is favoring the vehicle with lesser battery charge

capacity. This is the reverse of the technical optimization, which suggests more batteries for

better perfolmance. This gives the idea of the cost of the batteries. The cost and space of the

batteries constrain the lumber of batteries that can be can-ied along. Moreover, the floor of

the vehicle is to be strong enough to accommodate the batteries. One of the challenges in the

cui-sent research is 110w to accoinmodate these batteries. The manufacturers insist on no

sacrifice of con~fort of the passengers for giving roo111 for the batteries. So, the space

constraint is also significant for marketing and is also considered in this study. This would

7 7

give an idea of the practical feasibility of the quantity of on battery charge, which can be

carried along with the vehicle.

Developnlent of compact batteries at higher charge densities could be helpful in

nlaking the hybrid vehicles cost effective. Several other options like h e 1 cells as seconda1-y

source of power are also 011 the way.

I11 essence, this thesis supports the conclusion that parallel hybridization of the

dri\.etrain could help S W s and heavy trucks to improve fuel efficiency. The initial cost

outlays will be justified because of the cost savings in the long run. Moreover, the effect will

be larger on the heavy trucks than on the sports utility vehicles.

The optinluln designs from the results presented in the thesis are an average SL7'

\\-it11 a total power of around 150kW at 30 percent hybridization, meaning a combination of

S1 engine of 105KW and a motor of 35 KW powered with 50 battely modules. In the case of

full size SCTV \\.it11 a total poLver of 200 KW, the optimum percent hybridization is around

20%. This suggests that for SUVs, the motor of power ranging from 40 to 50 kU' in

combination \vith 50 battery c nodules could be sufficient for the optimum design.

At this point, it could be noted that the percent hybridization for Honda Insight is

20'!b, and that for Toyota Prius is around 30%, which are comparable to the results produced

in this study.

Similarly for heavy truck with total power of400K'&*, the optinlum percent

hybridization will be around 25%, with 50 batte1-y modules. This is because heavy trucks

recj~~ire large amount of po~ver initially to accelerate and hence they need higher motor

poLvsrs in cornpa-ison to their IC engine power. At this point in time, more batteries

7 8

techn~cally add value, but they are very expensive. But the research In that dn-ectlon could

niahe more batteries affordable.

6.6 Recommendations for further Simulation Studies:

1 . The thesis heavily supports the theory that hybridization adds value to heavy trucks. So,

further research of hybrid electric drivetrains for heavy vehicles could be interesting.

3. En~issiolls, wliicli play a very significant role in countries like US where tlie ernissioli

control laws are strict, are not dealt with in this tliesis. Since there will be stricter

emission laws in f ~ ~ t u r e , it is recommended that the emissions be considered in the works

related to tlie design of hybrid vehicles.

3 . The thesis supported tlie fact that the batteries being expensive cannot be used for adding

tecli~iical value to the vel-zicle. Since a lot of research is into fuel cells, they could be

examined as a potential substitute to or coniplement for conventional vehicles.

Some other studies related to this research area that could be done using ADVISOlI

include:

1. l 'he use of Series Hybrid Elect~ic d~ivetrains as a substitute for conventional drivetrains.

3. Diesel engines for sports utility vellicles could be an interesting study. Different

combinations ordiesel engines with fuel cells or batteries could be tested if they could

improve the file1 econolily and perforn~ance.

3 . '1'112 study of Continuously Variable Transiuission (CVT) for the increase of fuel

efticiency of hybrid electric vehicles could be another interesting topic.

4. The feasibility of pure electric vehicles could be tested using different batteries.

References:

1 Marshall Br~an's "Hon Stuff Works", infoimat~on fro111 the World uide web at

~ T T W h o w s h ~ f h orks com, June 2002

2 " Chrysler Motor Con~pany" ~~~fomnlation-retneved on 1 5 ' ~ Jan 2001 from the world

\T ~ d e n e b site at uuw chrvsler corn , June 2002

3 " , 4 u t o ~ eb", lnfoimat~on fi-om the uuw autoweb com, June 2002

3 " General Motors" lnfonllation retrieved on 1 jth an 200 1 from the v, orld wide u eb

site at uwx..gnl.com

5 . "Wichita Kenwoi-th, Inc." infoimation from the ~vorld wide web at

\~w~v.v,~ichitakenwo~tl~.con~, June 2002

6. "Dodge" infoimation retrieved on l j t h Jan 2001 fiom the world wide web site at

~ww.4adodge.com

7. " Idaho hTational Engineeline and Environmental Laborato~~." , information retrieved

from the world wide web on January 1 l th, 200 1 at

(hrt~:."ev.ii~el.~ov!sin~ple~~/desc.l~tml)

S. "Computer modelillg in the design and evaluation of electric and hybrid vehicles"

iilfo~nlatioil retrieved from the world u ide web at

(http:.'!ed~1cation.lai1l.go~~RESOURCES1Nh4SCC/education.htn1) , June 2002

9. "IEEE Transactions on Vehicular Technology" obtained from Ohio Link Research

databases fiom IEEE Transactions on Vehicular Technoloev. v 45, n 6. 1999, p 1770

1778.), June 2002

10. "National Renewable Energy Laboratories", Retrieved from the world wide web on

Decenlber 1 jth, 2000 at www.nrel.org

80

11. "Parametric Design of a Drivetrain of an ELPH vehicle", Electric and Hl'bl-id

b'ehicle desigl~ studies S,IE SP 1-743

13. "University of Colorado in Ford Hybrid Electric Challenge", Ford Hybrid Electric

Velzicle Clzallenge SA4E SP 980

13. ' ' Inlproving the Fuel Economy of SUVs through Diesel Technology and

Vehicle Improvements" Presentation of mini study for Dept. of Commerce and

DOE (Si'4195) Illfomlnation obtained from the NREL uebsite connecting to link

'Projects and Studies done using ADVISOR', June 2002

11. D. Assanis, G. Delagran~matikas, R. Fellini, Z. Filipi, J. Liedtke, N. Michelena, P.

Papalambros, D. Reyes, D. Rosenbaum, A. Sales, M. Sasena (19991, "Improving the

Fuel Econoiny of a Hyblid Electric Vehicle", Jourlzal of Mecha~zics qf Strzlctur-es and

Maclzines

15. "Optimal Design of Automotive Hybrid Powertrain Systems"

University of hlichigan, Paper for EcoDesign Conference in Tokyo (Y99j.

16. " Hawker Noif11 America" illfonnation obtained from the World Wide Web at

11ttp::I:\v~~11:.11epi.~om~basics!pb.hti11, June 2002

17. "3lorgantown Kational Supply. Inc" infommation retrieved on March ~ 3 ' ~ 200 1 fi-om

the world wide web at w\vw.rnns.con~.

Uib l io~raphv and Recommended Readinq:

(Itelated research articles that were read but not directly cited)

1 . Electric and Hybrid Vehicle Design Studies SAE SO 1243

2. T. Moore, "Tools and Strategies for Hybrid Electric Drive systems Optin~ization"

SA4E Pupel- 961660,1996.

3. Mathew R Cuddy and Keith B.Wipke, "Analysis of the Fuel Economy Benefit of

Drivetrain Hybridization", Retrieved from the world wide web Decembel- 2000 at

\vw\v.nrel.org.

3. R.Fellini, N.Michelena, M.Sasena and P.Papalambros, "Optimal Desi_g of

Automotive Hybrid Poweltrain Systems" Proceedings of EcoDesiglz '99: First

inteniational Sylllposiurn on Environmentally Conscious desigm and Inverse

Manufacturing. Tokyo, Japan, February, 1 3 , 1 9 9 9 , ~ ~ 400 405

5 . Y.Gao,K,Rahman,and M.Ehsani, "Parametric Design of the Drivetrain of an

Electrically Peaking Hybrid" S.4E pupel 970294,1997.

6. R.Riley,R.combene,M.D~~~~all,A.A Frank, "Hybrid Electric Vehicle Development at

University of Califolnia, Davis" 1993 Ford FIyhrirl Electric Vehicle clzallengc< SAE

SP 980

7. Willianl E. Kran~er , "Design of a Hybrid Electric Vehicle" 1993 Ford 17ybrid

Electric Velzicle clznllerzge SAE SP 980

S. D.Assanis,G.Delagra~nn~atikas,R,Fellii~i,J.Liedtke,N.Mocl~elena, P.Papalambros,

D.Reyes,D,Rosenabau~~~, A.Sales, M.Sasena, "An optimization Approach to I-Iybrid

82

Electric propulsion System Design", U~iiversity of Michigan, Ann Arbor. Retrieved

from the world mide web December 2000 at www.nrel.org

9. David J . .4ndres, Philip R.Guizeic, Robert A. Weinstock, "Hybrid Electric Vehlcle

Philosophy and Architecture" 1993 Ford Hjlbrid Electric J'ehicle chalIenge SkIE SP

980

10. Timothy C. More and Arnloiy B. Loind, "Vehicle Design Strategies to Meet PNGV

Goals"? SAIE 951 906.

11. C.W.Schwa~-tz, Faculty, Doug Callahan, and Noml Harrison, " A Hybrid Electric

Vehicle Concept", Lawrence Technological University. 1993 For-d H1,brid Electric

Tit.hicle challerzge Sa4E SP 980

12. Elisani, hlehrdad; Gao, Yiniin; Butler, Karen L. " Application of elect~ically peaking

hybrid (ELPH) propulsion system to a full size passenger car with si~liulated design

verification" IEEE Trunsuctioils on Velzict~lnl- Techlzology V48,n 6.1999,p1779 1787

13. "Ford Hybrid Vehicle challenge", SAE SP 980

13. "National Renewable Energy Laboratories", Retrieved from the world wide \r,eb on

Dece~nber 1 7'h, 2000 at ~ ~ s r w . m e l . o r g

15. "EV World", Retrieved fro111 the world wide web on December 171h ,2000 at

\v\ni.x\ ,E\world.com

16. "Marshall Brian's How Stuff JYorks", lnfo~mation from the World wide web at

~~~~w.liowst~iffworks.coni, June 2002.

17. " Autoweb", ilifolniation from the ww.autoweb.com, June 2002.

18. "Witchita Kenworth, Inc." information from the world wide web at

Appendices

Appendix A

.AD\-ISOR Documentation

-4DVISOR, NREL's ADvanced VehIcle SimulatOR, is a set of model, data, and script text

files for use uith Matlab and Simulink. It is designed for quick analysis of the performance

and fuel economy of conventional, electric, and hybrid vehicles. ADVISOR also provides a

bacliboile for the detailed simulation and analysis of user defined drivetrain components, a

starting point of verified vehicle data and algorithms fiom which to take full advantage of the

modcling flexibility of Simulink and analytic power of Matlab.

You may benefit fiom using ADVISOR if you want to:

estimate the fuel economy of unbuilt vehicles

learn about how con\-entional, hybrid, or electsic vehicles use (and losej energy

throughout their drivetrains

conlpare tailpipe emissions produced on a number of cycles

evaluate a control logic for your hybrid vehicle's he1 converter

-optimize the gear ratios in your transmission to minimize fuel use or maximize

perfomlance, etc.

The models in .4DVISOR are:

n ~ o s t l ~ . empirical, relying on drivetrain component input.'output relationships

measured in the laboratory, and

8 4

quasi static, using data collected in steady state (for example, constant torque and

speed) tests and cox~ecting them for transient effects such as the rotational inertia of

drivetrain components.

4DI7ISOR was preliminarily written and used in Noveinber 1994. Since then, it has been

niod~fied as necessary to help manage the US DOE Hybr~d Vehicle Propulsion System

subcontracts. Only in January 1998 was a concerted development effort undertaken to clean

LIP and doc~lme~lt ADVISOR.

Slllce then, researchers at

Chrysler Corp.

General Motors Co1-p.

AlliedSignal Autoinotive

Argonne National Laboratory

Naval Research Laborato~y

University of Califoillia Davis

University of Maryland

U~iiversity of Illinois Urbana/Charnpaign

and other research institutioils have used ADVISOR to predict the performance of their

vehicles, do studies on the effect of control strategy on enlissions and fuel use, among other

things.

8 5

1.2. Capabilities and intended uses

AD\'ISOR uses simple physics and measured component perfonnance to model existing or

imagined vehicles. Its real power, of course, lies in the prediction of the performance of

vehicles that have not yet been built. It answers the question "what if we build a car with

certain characteiistics?" ADVISOR usually predicts h e 1 use, tailpipe emissions,

acceleration perfollilance, and gradeability.

In general, the user takes two steps:

1 . Define a vehicle using ~neasured or estimated component and overall

vehicle data.

2. Prescribe a speed versus time trace, along n i th road gsade, that the vehicle

must follow.

.4DVISOK then puts the vehicle through its paces, making sure it meets the cycle to the best

of its ability and measuring (or offering the opportunity to measure) just about every torque,

speed, voltage, current, and pon.er passed from one component to another.

ADVISOR ss,ill allow the user to answer questions like:

Was the vehicle able to follow the trace?

How much f ~ ~ e l and/or electric energy were required in the attempt?

Vvllat were the peak powers delivered by the drivetrain components?

Qliat was the disti-ibution of torques and speeds that the piston engine delivered?

J h a t lvas the average efficiency of the transmission?

86

By iteratively changing the vehicle definition andior driving cycle, the user can go on to

answer questiolis such as:

At what road grade can tlie vehicle maintaill 55 niph indefinitely?

What's the smallest engine I can put into this vehicle to accelerate from 0 to 60 mph

in 12 s?

Ahat 's the final drive ratio that minimizes fuel use while keeping the 40 to 60 nip11

tinie below 3 s?

.4DVISOR's GUI and other script files answer many of these questions automatically, ~vhile

others require sollie custom programming on tlie user's part.

Because ADVISOR is n~odular, its component niodels can be relatively easily extended and

improved. For example, an electroclieniical model of a battery, complete with difhsion,

polarization, and the~lnal effects, call easily be put into a vehicle to cooperate with a motor

model that uses a nieasured efficiency map. Of course, developilig new, detailed models of

dril-errain components (or anytiling else, for that matter) requires an illtimate familiarity with

the eil\.ironn~ent, MATLL4B:'Simulink.

;\nalvsis. not design

ADVISOR was developed as an a~ialysis tool, aiid not a design tool. Its compo~ient models

are quasi static, and cannot be used to predict phenomena with a time scale of less than a

second or so. Physical vibrations. electric field oscillations and other dynamics cannot be

captured using ADVISOR.

87

As an analysis tool. ADVISOR takes the required speed as an input, and determines what

drivetrain torques, speeds, and powers would be required to meet that vehicle speed.

Because of this flow of informaticn back through the drivetrain, from tire to axle to gearbox

and so on, ADVISOR is what is called a backA7ard facing vehicle sin~ulation.

For\i:ard facing ~ e h i c l e simulations iriclude a model of a driver, who senses the required

speed and responds with an accelerator or brake position, to which the drivetrain responds

\\,ith a torque. This tjpe of siniulation is well suited to the design of control systems, for

example, down to the integrated circuit and PC card level-the implementation level.

ADVISOR is well suited to evaluate and, by iterative evaluation, design control logic. By

control logic, we mean something like "When the engine torque output is low and the battery

state of cl-iarge is high, turn off the engine." The control logic, with which ADVISOR can

work, is about what you want the vehicle to do. The control systen~, beyond ADVISOR'S

pur\.ie\v, is about how to make the vehicle do what you want.

Po~ver bus for electric power transfers

I11 electrical components' conin~uliication with each other, ADVISOR deals in poLver, and

not in voltage and current.

Drive axle is fi-oiit axle oniv

The vehicle dyiamics calculations required for traction control and the wheel slip model

assume that the front axle is the only drive axle. Simple steps can be taken to correct the

n.eig111 transfer calculatioii if you wish to model a rear drive vehicle. Modeling a four wheel

drive \-ehicle requires iilvolved Simulink reprogramming. Please contact NREL if you have

such needs.

2.1.1 Defining a vehicle

Start takes you to the input figure. The input figure opens and you will see the default values

for a specific vehicle.

Drivetrain selection

Fro111 the drivetrain popup menu you will be able to select the drivetrain configuration of the

vehicle (Series, Parallel, etc.) which will cause the schematic of the vehicle configuration ill

tlie left portion of the figure to change accordingly. This will also modify which conlponents

are a\,ailable for the type of drivetrain chosen.

Selecting con~ponents

After selecting the drivetrain configuration, all the componellts of the vehicle can be selected

using the popup menus, or by clicking on the coinponeilt in the picture. To the left of the

component popup illenus is a pushbutton that will allow you to add or delete coinponents by

selecting their coisesponding listed m files. The m file of a specific component can be

accessed for vie~ving or modifying fi-om either the component pushbutton or by clicking on

tlie component of the picture.

Editing Variables

After selectiilg all the desired conlpoilents for the vehicle, scalar input variables can be

~nodii ied. One way this can be done is with the variable list at the bottom of the figure and

the Edit Var. button. First select the variable to change and then click the edit button to

cllange its value. The default value is always shown for your reference. The View All button

allows you to see all of the variables you have altered. You can click on the help button to

see a biief description and the units used for the input variables.

S 9

A second ~5.ay in which you can edit variables is by typing in a desired value in the edit

boxes next to the conlponent. For example, adjusting the maximum power of a fuel

conyerter adjusts the variable fc-trq-scale, or increasing the peak efficiency increases tlie

~ a r i a b l e fc - eff - scale accordingly.

A final \Yay to edit the mass of the vehicle is to use the override mass button. The calculated

mass is ignored and tlie value input into the box is used instead.

Loading and Savi~lg vehicle confizurations

To load or save a particular vehicle configuration click on the Load Vehicle button on tlie top

of the figure or click on Save at the bottom of the figure. The file will be saved in the foniiat

'filename-in.ml. A saved vehicle call be accessed by pushing the load button.

\-ie\ving conlponent information

At the bottoln left poi-tion of the figure there is a popup menu and axes with the ability to

vie\!. infoiiliation on compoilelits such as their efficiency maps, emissions maps, fuel use

maps. etc. These are plotted along with their maximum torque envelopes where appropriate.

,411~ coniponeiit ni file can be viewed by clicking the conlponent buttons.

Auto Size

The auto size button takes tlie selected vehicle and adjusts vehicle parameters until it meets

acceleration and gradeability goals. The parameters it alters are the fuel converter torque

scale (fc - trq_scale), the motor controller torque scale (mc - trq-scale), the number of energy

storage system modules, and the vehicle mass. The minimum torque scale is set so that its

peak pon.er output is 45 kW. The n~lnlber of battery modules is limited to yield a maxilliiiln

nominal voltage of 380 V. The default performance targets are maintaining at least a 6%

90

grade at 5 5 mph, and obtaining less than a 12 second 0 60 mph time, 23.4 second 0 85 nlph

time, and 5.3 second 40 60 mph time.

Back and Continue Buttons

The Back button will take you to the opening screen, losing all unsaved infomnlation, and the

Corztirllle button will take you to the simulation setup figure.

2.1.2 Running a simulation

The s~mulation setup figure glves ~ O L I several options on how to test the currently defined

vehicle

Drive Cvcle selection

If the drive cycle radio button is selected you can use the pull down menu to select from a

11st of available driving cycles. You can then select how many times you want the cycle

repeated as well as if you want SOC coisection. Initial conditions can also be set from here.

The filterlilg allows you to smooth out the selected drive cycle.

T I - I ~ ~ Builder

A cycle can be created by combilling many different cycles back to back uslng t h ~ s

f~~nctionality. This new cycle is then saved in the normal cycle fornlat and can be run as

such.

SOC Corsect

There are hvo SOC toll-ect optlons: linear and zero delta. The Linear SOC correction routine

I-LLIIS hvo simulations-one that gives a positive change in the state of charge and one that

gives a negative change in SOC. The co~sected value of the variables of interest (e.g. miles

pzr gallon and en~issions) are then interpolated from the zero change in SOC fro111 a linear fit

to the two data points. The Zero Delta correction routine adjusts the initial SOC until the

sinlulation nun yields a zero change ~ I I SOC +i a 0.5% tolerance band.

Constant Road Grade

By select~ng the checkbox you can lull the dnbe cycle uslng a constant road grade In place of

the drive cycle's elevation profile.

Interactive Sin~ulation

Selecting the Interactive Simulation checkbox causes a real time interactive sin~ulation

inrerface to activate while tlie sinlulation is running.

Multiple Cvcles

You can speed up the process of l-unning many different cycles with the same initial

conditions using this functionality. hlultiple Cycles saves tlie setup information including

initial conditions and then runs each of the cycles selected and saves the results. From the

results figure you can access all the different results ~vith the aid of a results list.

Test Procedu1.e

If the test procedure radio button 1s selected you can use the pull down menu to select ~vhat

l<ind of test to 11111.

Acceleration Test

By selecting this checkbox, an acceleration test will be run in addition to the chose cycle.

Acceleration times, maxiinurn accelerations. and distanced traveled in 5 seconds will be

displayed in the results figure. This test will be run in addition to the chosen cycle. To see

the second by second outp~lt of an acceleration test, choose the CYC - ACCEL from the cycle

Help on Acceleration Test

The acceleration test routine in ADVISOR will detennine the acceleration performance of

the current vehicle. The test routine can be accessed both from the GUI and the Matlab

command window.

Frorn the GUI ...

An acceleration test can be pel-fomnled via the Simulation Setup wiildow (Fig A. 1 ). By

clicliing .4ccel Optiorzs the Acceleration Test Advanced Options window appears. Note that

the Constraint and Tolerance items are only visible and accessible when the Accel Options

button is pushed from the Autosize Setup window.

The shift delay checkbox allows you to override the current shift delay during the

acceleration test. The Enable Systems set of radiobuttons allows you to identify any systems

th;it sliould not participate in the test. For example, you could determine the acceleration

pel-i'oli~~ance of your parallel hybrid in a worse case situation when you only have one power

source, engine only or batte~y only. As long as the battery is enabled, the initial state of

charge (SOC) can be specified by the user. The initial setting defaults to 50% of the usable

range (cs - lo-soc to cs-hi-soc). The Mass Parameters allow you to override or adjust the

vehicle mass during the acceleration test. By overriding the mass you will fix the mass at the

specified value and by adding to the curl-ent mass you will add the specified amount to

cun-ent mass. The results section allows you to specify the acceleration criteria of interest.

Awilable options include 3 speed range acceleration times, a distance in a set amount of

time, time in a set anlol~nt of distance, and max acceleration rate, and a top speed. While

perfol-ming an autosize these co~lditions can be used as constraints.

Fro111 the Simulation Setup screen selecting the Accelei.atioiz Test checkbox runs an

acceleration test during a drive cycle. To run an acceleration test without running a drive

cycle, select Test Procedure and then TEST - ACCEL frorr, the pulldown menu. If run as a

test procedure the Results screen will provide access to the time dependent variable

Results are reported in the Results window.

Fig A. 1 Acceleration Test Advanced Options window

9 4

Gradeabili tv Test

If the gradeability checkbox is selected, a gradeability tesz will be run in addition to the

chosen cycle The grade displayed in the results figure will be the maximum grade

maintainable at the input mph.

Parametric Studv

To see the effect that up to three variables have on the vehicle, select a parametric study

The lou and high values nlay be set, as nrell as the number of points desired for that

~.ariable. A parametric study runs a set of simulations to cover the matrix of input points,

such that if 3 variables are selected with 3 points each, 27 simulations will run.

Load Siin Setup

A previously saved sirnulati011 setup can be reloaded using the Load Sint. Setup push

button. See a below.

Optimize cs vars

The Oytinzi~e cs vars push button opens the control strategy optimization setup windo~v.

Checking the radio boxes selects the d e s i g variables used to optimize for the chosen

objectives and constraints below.

a Sa\ es the s~n~u la t lon setup.

Run

To run the siinulation click Run and wait for the results figure to popup

2.1.3 Looking at outputs

Results Figure

-The results figure presents some summa17 results (fuel sconomy, emissions, total distance,

etc.) and allows the user to plot up to four time series plots by selecting a variable from the

popup menu. If the acceleration and gradeability checkboxes were picked in the simulation

setup screen, appropriate results will also be displayed.

By clicking the Energy Use Figure button, a new figure is opened showing how energy was

used and transfel-red for the vehicle during the simulation, The Output Check Plots button

pulls up plots that show the vehicle's pe r fo~~~lance , some of which are not available under the

time series plots. The Replay button replays the dynamic interactive interface. Replay is not

available for Test Procedures or Multiple Cycles.

Parametric Results Figure (Fig A.2)

The parametric results figure plors the summary results as a function of your chosen

\,ai-iableis). For hvo and three variable studies, the Rotate button allows you to view the plot

~I-OIII all sides. For three \.ariable studies. you can plot any slice of the results.

Appendix B

Alatlab Files

The files wntten in Matlab for the si~nulation of the three vehicle platforms are given belo\+.

hlatlab file is forl5OkW mid size SUV of 136 kg cargo, SI engine 95 and motor75 with lead batteries .

O;, This file is for U.6 1jOltW Illid size suv of 136 kg cargo, Si engine 95 and motor75 with ?"lead batteries . s=[O 30 45 60 80 100 1251

141motor=200 IC=200; for i=1:3

cm(i: l)=0; end

for i=1:3 for p=2 : 7

cm(i,p)=s(p)*lj + IC;

94 battery cost and space (75s per cell and 3.65 liters of space) for p=2.:7

%Replacemsilt cost in 13 years if replaced 5 times (each time 60% of initial cost) for i=1:3

for j=l :7 rc(i.j)= 5*cb(i,j j"0.6;

end end

end

s=s,'1.5 mpg( 1,:)=[17.6 23.7 24.9 26.4 28.4 31.2 39.21 % 25 modules mpg(7,:)=[17.6 23.7 24.9 26.4 28.4 31.6 40.71 %35 illodules 1npg(3,:)=[17.6 23.5 24.8 26.2 28.2 31.6 38.21 %50 modules

plot(s,mpg(l ,:I,' *') hold 011;

pause; plot(s.mpg(?,:),'r 0') hold on; pause; plot(s,mpg(3,:),'g +') shg; pa~lse;

~r( l , . )=[S.95.3 8.79.2 10.3 11.8 15.21 '%25modules at(2, )=[8.9 8.1 8.3 8.6 9.4 10.4 12.41 ?/o 35 modules at(3,:)=[8.9 8.4 7.9 8 8.5 9 1 10 31 %, 50 modules elf; plo1(s,at(l ,: 1,' *I)

hold on, pa""; plot(x,at(2,:),'r of) hold on, pause: plot(x.at(?,:),'g +') hold on: pause; clf o.:op 11111~11"

for 1=1:3 for :7

op(i,j)=0.3*mpg(i,j)/inpg(l, 1 )+0.7*(at(1 ,1)/at(i,j))A2; %cost savings for 14 years cosavinys(i,j)= [ l /mpg(l , l ) l/mpg(i,j)]*12000*1.40*14 cb(ij) crn(ij) rc(ij); cosavingso(i,j)= [l!mpg(l, 1) 1/111pg(i,j)] * 12000*1.40*14 cb(ij) cm(ij);

costratio(ij)= 250001 [25000 cosavings(i,j)];

spaceratio(i,j)= [4000 cs(ij)]/4000; perf~llratio(i,j)= at(1 , l)/at(ij);

cop(i,j)= 0.45*25000/ [25000 cosavings(i,j)] + 0.45*at(l,l)/at(i,j)+O. 1 *[4000 cs(i,j)]/4000; copo(i,j)= 0.45"250001 [25000 cosavingso(i,j)] + 0.45*at(l,l)/at(i,j)+0.1 *I4000 cs(ij)]/4000; vc(i,j)= 25000+cb(i,j)+cm(i j);

end end cl f; %tecIinical oiptiillulll plot%

plot(x,op(l,:).' *') hold 011;

pause plot(x,op(2,:),'r 0') hold on; pause; plot(x,opj3,:),'g +') hold on: pause; c l t %Vehicle Cost figure(2) plot(x,vc(l ,:),I *') hold on; pause plot(x,vc(2,:),'r 0') hold on; pause; plot(s.vc(3,:),'g +') shg pause: clf 96 Cost Optl~nulll Plot plot(s,cop(l,:),' *') hold on; pause plot(x,cop(2,:),'r 0') hold on; pause; plot(x,cop(_?,:),'g +') hold oil; pause; shg cl f: "G Colllparisio~l of teclulical and cost optimizaiio~l plots plot(s.op(1 ,:),I *') hold on; pause; plot(x,cop(l,:),' 0') hold on; p a ~ ~ s e ; shg c1e 9.0 Ratio Plot plot(x:costratio(l ,:),I *') hold on; pause plot(x,perf~~lratio(l ,:),'r *') hold 011; pause

plot(s,spaceratlo(l,:),'g *') hold on: pause plot(x,cop(l ,:),'black *') hold on; pause; c l t

($6 Cornparision of cost optimization with and with out low cost batteries plotj~,cop(l ,I),' *') hold on; pause;

plot(s,copo(l ,:),I 0') hold on; pause; shg

Matlab file for 200k\IJ mid size suv of 636 kg cargo, Si engine 95 and motor75 withlead batteries.

(% This file is ['/;)200ErW mid size suv of 636 kg carzo, Si engine 95 and 111otor75 with %lead batteries . s=[0 40 60 SO 100 120 1601

0,6Imotor=700 IC=200; for i=1:3

~111(1,1 )=o; end

for i=1:3 for p=2:7

c~n(i.p)=s(p)* 15 + IC;

end end

O/h battery cost and space (75$ per cell and 3.65 liters of space)

for 17'2::

cb(1 ,p)= 25*75; cb(2.p)= 50*75; cbi3,p)= 100*75; cs(l.p)= 25*3.65; cs(?,p)= 50*3.65; cs(3,p)= lOO"3.65; end

?'oReplacement cost in 14 years if replaced 5 tinles (each time 60% of initial cost) for i= 1 :3

for j=l:7 rc(i J)= 5* cb(ij)*0.6;

end end

s=s12 nlpg(l,:)=[13.6. 18.6, 19.6, 20.8. 22.0, 23.3, 28.81 %25 modules mpg(?.:)=[13.6, 18.6, 19.6. 20.8, 22.1, 23.5, 30.11 9650 modules mp9(3,:)=[13.6, 17.9, 19.0, 20.1, 21.2, 22.7, 29.81 %I00 illodules

ploti x.mpg(l ,:),I *') hold on; pause; plot(~.mpg(2,:), 'r 0 ' )

hold on; pause; plot(~.lllp$!(3.:),~ shg: pause:

attl.:)=[8.8 8.4 8.9 9.6 10.5 11.8 16.31 % 25 ~noduies at(2,:)=[8.8 8.1 8.2 8.6 9.4 10.4 12.41 % 50 111odules at(3,:)=[8.8 8.9 8.3 7.8 7.5 7.7 8.41 % 100 modules

cl f; plotjs,at(l::).' *') hold 011; pause: plot!s.at(,,:),'r o') 11old on: pause; plot(x.at(3,:).'g +'I shg ; pause:

ohoptiilluil~ for i=1:3

for j= 1 :7 op(i,j)=0.3*111pg(iJ)/il1pg(l,l)+O.7*(at(l, l)/at(ij))"2

Ohcost savings for 14 years cosavings(i,j)= [ l / i~lpg( l , 1) llmpg(i,j)]*12000*1.40* 14 cb(ij) cni(ij) rc(ij)

cop(ij)= 0.45*250001[25000 cosavings(i,j)] + 0.45*at(l ,I)/ at(ij)+O. 1 *[4000 cs(i,j)]/4000;

vc(ij)= 25000+cb(i,j)+cm(i j); end

end

"io Technical Optiin~lill

plot(s,op(l,:),' *') hold on; pause

plot(x,op(2,:),'r o') hold on; pause;

plot(s,op(3,:),'g +') hold on; pause; clf;

%Vehicle Cost figure(2) plot(s,vc(l , : ) , I *') hold on; pause

plot(s,vc(2,:),'1- 0')

hold on; pause;

s11g pause; clf

"/cost oiptimum plot% figure(3) plot(x,cop(l ,:),I *') hold on; pause

plot(x.cop(3,:),'r of) hold on: pause;

plot(x,cop(3,:),'g +') hold on; pause; c l t

% Ratio Plot plot(s,costratio(l ,:),I *') hold on; pause plot(x,perfi~ratio(l,:),'r *') hold on; pause plot(x,spaceratio(l,:),'g *') hold on; pause plot(s,cop(l ,:),'black *') hold on; pause

Matlab file for 4OOk\V truck of 8000 kg cargo,CI engine 121 and motor 45 withlead batteries.

%0300kM7 tnick of 8000 kg cargo, cl englne 121 and rnotor 75 w ~ t h 9Slead batteries . x=[050 100125 150200250275 3001

?,hImotor=200 IC=200; for 1=1:3

cm(i,l j=0; end

for i=1:3 for p=7 :9

cm(i,p j=x(p)* 15 + IC;

O ' o b~ t t e r ) cost 2nd space (755 per cell and 3.65 liters of space) for p=2:9

cbi l .pj= 50*75: cb(2,p)= 100*75; cb(3,p)= 150*75; cs(l,p)= 50*3.65; cs(?,pj= 100'9.65; cs(3,p)= 150*3.65; end

?"Replacement cost in 14 years if replaced 5 tilnes (each time 60% of initial cost) for i=1:3

for j=l:9 rc(i.j)= 5* cb(ijj*0.6;

end end

s = x 3 mpg(1.:)=[5.2 6.3 6.4 6.6 6.7 7.7 9.4 10.3 12 ] %50 lllodules mpg(3.:)=[5.2 6.2 6.7 6.8 7.0 7.8 9.9 11.6 13.81 %I00 modules nlpg(3.:)=[5.2 6.3 6.7 6.9 7.0 8.0 10.0 11.7 14.31 %I50 nlodules

plot(x.mpg(l,:),' *') hold on; pause; plot(x,~l~pg(?,:), 'r of) hold on; pause: plot(s,mpg(3,:),'g +') s11g; pause;

clf- plot(x,at(l ,:),I *') 11old on; pause; plot(s,at(2,:),'r 0') hold on; pause; plot(s,at(3,:),'g +') shg; pause;

"bopt~murn for i=1:3

for j=l:9 op(i ,j)=0.3*1i~pg(i,j)/mpg(l,l)+0.7*(at(1 ,l)/at(i,j))/'2

%cost savings for 14 years cosavings(i,j)= [1111ip~(1,1) 1/1i1pg(i,j)]*l2000* 1.40*14 cb(i,j) cln(i,j) rc(i,j);

plot(x,op(:l,:).' " I )

ho!d on; pause

plot(s,op(?,:).'r 0') hold on; P3LlSZ.

plot(x,op(3,:).'g ") hold on; pause: clf;

0 , - ,,o\ ellcle cost plot(x,vc(l,:),' *') hold on; pause

plot(s,vc(2,:),'r o') hold on: pause;

plot(x.\ c(3,:),'g +') hold on; pause:

';cost oiptlmurn plot96 pIot(x,cop( 1 , : ) , I *I)

hold 011: pause

plot(s,cop(?,:),'r 0') hold on: pause;

9.0 Ratio Plot plot(s.costratio(1 ,:).I * I )

hold on; pause plot(x,perfi~uat~o(l,:),'r *I) hold on; pause plot( u,spacerat~o(l ,:),'g *') hold 011; pause plot(x.cop(1 ,:),'black *I) hold on; pause

Rlatlab File for 150kW Mid size SUV which includes the effect of weightincfactors on technical and cost optimum d e s i ~ n .

Oio Tills file is for l5OkW mid size suv of 136 kg cargo, Si engine 95 and motor75 with

%lead batteries . x=[O 30 35 60 80 100 12.51

o/~Imolor=lOO 1C=100: for 1=1:3

cm(i,l)=O; end

for I= 1 :3 for p=2:7

cm(i,p)=x(p)* 15 + IC;

% batrery cost and space (75$ per cell and 3.65 liters of space) for p=2:7

9bReplacement cost ill 14 years if replaced 5 times (each tillle 60% of initial cost) for i=1:3

for j=l :7 rc(i.j)= 5*cb!i3j)*0.6;

end end

plot(x.mpg(1 ,:),I-*') hold on; pause; plot(s,mpg(2,:),'r-0') hold on; pause; plot(x,111pgi3.:),'g-+') shg: pause;

at(l,:)=[S.9 8.3 8.7 9.2 10.3 11.8 15.21 % 25 modules at(?,:)=[S.9 8.1 8.2 8.6 9.4 10.4 12.41 l'o 35 modules at(3,:)=[8.9 8.4 7.9 8 8.5 9.1 10.31 % 50 modules

c l t plot(s.atj1 , : ) , ' - * I )

Ilold on; pause: plot(x.at(?,:).'r-0') hold on; pause; plot(x,at(3,:),'g-+') hold on; pause:

clf

l4optimum for i=1:3

for j=l:7 opji,j)=0.~~mpg(i,j)iimpg(1,1)+0.7*(at(l .l)!at(i.j))"2;

%cost sa\ mgs for 14 years

cop(ij)= 0.45*25000,/ [25000 - cosavings(ij)] 0.45*at(l,l)Iat(i,j)+O. 1*[4000-cs(i,j)]:3000; copo(i.j)= 0.45*25000; [15000 - cosavingso(i,j)] t 0.45*at(l,l)/at(i,j)-0.1*[4000-cs~i,j)];4000; vc(i,j)= 25000+cbji,j)-c111(i,j); end end cl f ;

Oioteclln~c~l olptimum plot% plot(x.op(1 .:),I-*') hold 011: pause plot(x,op(?,:),'r-o') hold on; pause; plot(x,op(3,:),'g-+') hold on; pause; clf:

94\'ehlcle Cost figure(2) plot(s,vc(l,:),'-*') hold on: pause plot(u,\ c(2,:),'r-0') hold on; pause; plot(\,\ ci3,:),'g-+') shg pause; clf

% Cost Optimum Plot plot(x,cop(l ,:),'-*I)

hold 011; pause

plot(x,cop(2.:),'r-0') hold 01.1;

pause:

plot(x,cop(3.:),'g-+') hold on:

pause; shg

Oi; Cornparision of teclulicai and cost optinlizatio~l plots

plot(x,op(l,:>,'-*'> hold on; pause;

plot(x.cop(1 ,:),I-0') 11old on; pause; shg clf;

'I6 Ratio Plot plot(x,costratio(l ,:),'-*I) hold on; pause plot(x,perf~iuatio(l ,:),?-*I) hold on; pause plot(x,spaceratio(l ,:),'g-*I) hold on; pause plot(x,cop(,l ,:),'black-*') hold on; pa""; clf;

C o ~ l l p a ~ i s ~ o n of cost opti~llizat~oll with and with O L I ~ low cost batteries ]7lot(\.cop(l ;),I-*') hold on; pause, plot(x,copo(l ,:),I-0') hold on; pause, shg; c 1 f-,

% Co~llparisioll of Technical Optimum Peaks with Different Weighting Factors

?/ooptimum for i=1:3

for j= 1 :7 opl(i.j)=O. 15*mpg(i,j)!1l~pgjl,1)+0.85"(at(l,l)iat(i,j))~2;

opj(ij)=0.45 *mpg(iJ)/mpg(l ,I)-t0.55*(at(l: l)/at(i,j))^2; end: end plot(s,opl (l,:),'-*') hold on: pause plotix,op2(1~: j,'-*') hold 011; pause 1-71or(x.op3(1 ,:),'-*I) hold on; pause plot(x,op4( 1 ,:),I-*') hold on; pause plot(x.op5(1 ::),I-*I)

hold on; pause; clf: 9'0 Co~llparisioll of Cost Optiiilulll Peaks for Different weiglitingFactors for i=1:3

for j=l:7 copl(i,j)= 0.15*25000/ [25000 - cosavings(i,j)] + 0.65*at(l ,l)/at(i,j)+O. 1*[4000-cs(i,jj]/4000; cop2(i,j)= 0.35*25000/ [25000 - cosavings(i,j)] +- 0.55*at(l ,l)/at(ij)+O. 1 *[3000-cs(i,j)]/4000; cop3(i.j)= 0.45*25000/ [25000 - cosavi~~gs(i.j)] + 0.45*at(1 ,l)Iat(i,j)+O. 1*[4000-cs(ij)]i4000; cop4iij)= 0.55*250001' [25000 - cosavings(i,j)] + 0.35*at(I,l)/at(i,j)+O. 1 *[4000-cs(ij)]/4000; copj(iJj= 0.65*250001[25000 - cosavings(i,j)] + 0.2iUat(l , l jiat(ij)+O. 1*[4000-cs(i.j)]i4000; end; end plot(s.cop l(1 ,:),'-*I) hold on: pause plot(x,cop?(l ,:),I-*') hold on: pause plot(x,cop3(l ,:),I-*') hold 011;

pause plot(x,cop4(1 ,:),'-*I) hold on; pause plot(,x.cop5(l , : ) . ' - * I )

ABSTRACT

MADIREDDY ML4DHL4VA4 RAO. MastersDecember 2002

Mechanical Engineering

Analvtical Desien of a Parallel Hvbrid Electric Powertrain for Sports Utilitv Vehicles and

H e a ~ ~ v Trucks

Director of Thesis : Dr. Gregory E' ~remer

In conventional vehicles, the entire power is derived from the IC engine. so, it is

obligatory to size the engine larger than necessary for its cruising speed. The engine is

to be designed to account for peak. power requirements like acceleration. This over sizing

the engine shifts the operating point from its efficient zone and this adversely affects the

fuel economy and emissions. The idea of hybridization is that a part of the total power

required can be replaced by an auxiliary power source, generally a motor powered by

batteries. Hence. the IC engine call be designed for average load and can be operated with

better fuel efficiency.

A simulation tool called ADVISOR '(Advanced Vehicular Simulator) is used for

this study. The software takes the vehicle input and the drive cycle from the user,

simulates the vehicle drive and gives fuel economy, acceleration performance and

emissions. In this study. each of the three vehicle platforms (light SUV, full size SLV

and Heavy Truck) is selected and a reasonable power level for that vehicle platform is

taken from the data of the current conventional vehicle type. The powertrain is then

hybridized by replacing (in steps) this power by an equivalent motor power and a

simulation is run. such simulatiolls are run in Advisor at three different battery charge