ENERGY MANAGEMENT SYSTEM FOR BATTERY HYBRID ELECTRIC

VEHICLE USING SUPERCAPACITOR

AREE WANGSUPPHAPHOL

UNIVERSITI TEKNOLOGI MALAYSIA

PSZ 19:16 (Pind. 1/07)

DECLARATION OF THESIS / UNDERGRADUATE PROJECT PAPER AND COPYRIGHT

Author’s full name : ________________________________________________

Date of birth : ________________________________________________

Title : ________________________________________________

________________________________________________

________________________________________________

Academic Session : ________________________________________________

I declare that this thesis is classified as :

I acknowledged that Universiti Teknologi Malaysia reserves the right as follows:

1. The thesis is the property of Universiti Teknologi Malaysia. 2. The Library of Universiti Teknologi Malaysia has the right to make copies for the purpose

of research only.

3. The Library has the right to make copies of the thesis for academic exchange.

Certified by :

SIGNATURE SIGNATURE OF SUPERVISOR

(NEW IC NO. /PASSPORT NO.) NAME OF SUPERVISOR

Date : Date :

NOTES : * If the thesis is CONFIDENTAL or RESTRICTED, please attach with the letter from

the organization with period and reasons for confidentiality or restriction.

UNIVERSITI TEKNOLOGI MALAYSIA

CONFIDENTIAL (Contains confidential information under the Official Secret

Act 1972)*

RESTRICTED (Contains restricted information as specified by the

organization where research was done)*

OPEN ACCESS I agree that my thesis to be published as online open access

(full text)

“We hereby declare that we have read this thesis and in our opinion this thesis

is sufficient in terms of scope and quality for the award of the degree of Doctor of

Philosophy (Electrical Engineering)”

Signature : ………………………

Name : Assc. Prof. Dr. Nik Rumzi Bin Nik Idris

Date : 28 April 2019

Signature : ………………………

Name : Assc. Prof. Dr. Awang Bin Jusoh

Date : 28 April 2019

Signature : ………………………

Name : Nik Din Bin Muhamad

Date : 28 April 2019

BAHAGIAN A – Pengesahan Kerjasama*

Adalah disahkan bahawa projek penyelidikan tesis ini telah dilaksanakan melalui kerjasama

antara _______________________ dengan _______________________

Disahkan oleh:

Tandatangan : Tarikh :

Nama :

Jawatan :

(Cop rasmi)

* Jika penyediaan tesis/projek melibatkan kerjasama.

BAHAGIAN B – Untuk Kegunaan Pejabat Sekolah Kejuruteraan Elektrik

Tesis ini telah diperiksa dan diakui oleh:

Disahkan oleh Naib Pengerusi di Sekolah Kejuruteraan Elektrik :

Tandatangan :

Tarikh :

Nama : PROF. MADYA DR. MOHAMED AFENDI BIN MOHAMED PIAH

Nama dan Alamat Pemeriksa Luar :

Prof. Madya Ir. Dr. Dahaman bin Ishak

School of Electrical &

Electronic Engineering

Engineering Campus

Universiti Sains Malaysia

14300 Nibong Tebal

Pulau Pinang

Nama dan Alamat Pemeriksa Dalam : Prof. Madya Dr. Shahrin bin Md Ayob

Sekolah Kejuruteraan Elektrik,

Fakulti Kejuruteraan,

81310 UTM Johor Bahru

UTM Johor Bahru

i

ENERGY MANAGEMENT SYSTEM FOR BATTERY HYBRID ELECTRIC

VEHICLE USING SUPERCAPACITOR

AREE WANGSUPPHAPHOL

A thesis submitted in fulfillment of the

requirements for the award of the degree of

Doctor of Philosophy (Electrical Engineering)

School of Electrical Engineering

Faculty of Engineering

Universiti Teknologi Malaysia

APRIL 2019

ii

DECLARATION

I hereby declare that this thesis entitled “Energy Management System for Battery

Hybrid Electric Vehicle using Supercapacitor” is the result of my own research except

as cited in the references. The thesis has not been accepted for any degree and is not

concurrently submitted in the candidature of any other degree.

Signature : ………………………

Name : AREE WANGSUPPHAPHOL

Date : APRIL 2019

iii

DEDICATION

This thesis is dedicated to my parents and sisters, who supported me very well in all

manners. It is also dedicated to my wife, my sons; DANISH, CHAMIL, and

YASEEN, who encouraged me to conduct the reseach until successful.

iv

ACKNOWLEDGMENTS

All praise and thanks are due to Allah, and peace and blessings of Allah be

upon our prophet, Muhammad and upon all his family and companions. Thanks to

Allah who gives me good health in my life and thanks to Allah for everything. Without

help of Allah, I was not able to achieve anything in this research.

In preparing this thesis, I was in contact with many people, researchers,

academicians, and practitioners. They have contributed towards my understanding

and thoughts. In particular, I wish to express my sincere appreciation to my main

supervisor, Assoc. Prof. Dr. Nik Rumzi Nik Idris, for encouragement, guidance,

critics, advice and supports to complete this research. I am also grateful to my co-

supervisor Assoc. Prof. Dr. Awang bin Jusoh and Mr. Nik Din Muhammad for their

precious advice and comments.

In addition, I am grateful to Dr. Ahmad Saudi Samosir for encouragement and

support during at the early stage of this research. My sincere appreciation also extends

to Islamic Development Bank (IDB) who provides the 3 years Ph.D. Merit Scholarship

for me and expenditures for my family, UTM-PROTON Future Drive Laboratory and

all my colleagues Dr. Ibrahim Alsofyani, Dr. Tole Sutikno, Dr. Mohammad Jannati,

Dr. Low Wen Yao, Mr. Sajad Anbaran, Dr. Ali Monadi, and Ms. Akmal for the support

and incisive comments in making this study a success. Their views and tips are useful

indeed. Unfortunately, it is not possible to list all of them in this limited space.

v

ABSTRACT

The propulsion system of battery electric vehicle (BEV) requires high power

from the battery during acceleration and supplies high regenerative braking power to

the battery while braking. As such, the battery, which is the main energy storage of

BEV, consistently has to withstand high dynamic power flow that could shorten its

lifespan. To overcome this problem, a hybrid energy storage system (HESS)

consisting of the lithium-ion battery (LB) and a supercapacitor (SC) connected via a

bi-directional DC-DC converter is proposed for the BEV – which is called as the

battery hybrid electric vehicle (BHEV). In this thesis, new energy management control

strategies for BHEV are proposed. In order to fully utilize the capability of the SC in

capturing the kinetic energy as well as supplying the acceleration power to the BHEV,

two methods of calculating the capacitance for the SC which is called the Acceleration-

based Design (ABD) and Deceleration-based Design (DBD) are introduced. These

methods are based on the principle of conservation of energy which balances the

energy stored in the SC and the kinetic energy of the vehicle, and at the same time

takes into account the losses involved in charging and discharging processes of the SC.

From these two methods, two energy management control strategies are developed and

applied to the BHEV. The power and energy flow between the LB, SC and the

propulsion load is controlled via a closed-loop control of the SC current; the SC current

references are generated based on the ABD and DBD approaches. Simulations of

actual-scale BHEV are performed using Matlab/SIMULINK based on the Maximum

Acceleration driving cycle and Extra Urban Driving Cycle (EUDC). Performances of

the proposed strategies are evaluated in terms of battery peak power reduction, voltage

variation improvement, and energy consumption of the battery. Finally, the proposed

methods are verified in terms of feasibility and practicability by conducting small-

scale experiments and simulations. Based on the results obtained from the simulations

and experiments, it is found out that BHEV-DBD gives the best performance in terms

of peak battery power reduction, voltage variation improvement and battery energy

consumption; compared to the conventional BEV, improvements of up to 46%, 3.5%

and 23% respectively, are achieved.

vi

ABSTRAK

Sistem penggerak untuk kenderaan elektrik bateri (BEV) memerlukan kuasa

yang tinggi dari bateri semasa memecut dan membekalkan kuasa brek yang tinggi pada

bateri semasa brek. Oleh itu bateri, yang merupakan penyimpan utama tenaga untuk

BEV, sentiasa menghadapi dinamik kuasa tinggi yang boleh memendekkan jangka

hayatnya. Untuk mengelakkan masalah ini, sistem penyimpanan tenaga hibrid (HESS)

terdiri dari bateri lithium-ion (LB) dan superkapasitor (SC) yang disambung melalui

penukar DC-DC dwiarah dicadangkan untuk BEV – yang dipanggil sebagai kenderaan

elektrik bateri hibrid (BHEV). Dalam tesis ini, strategi-strategi kawalan pengurusan

tenaga yang baharu untuk BHEV dicadangkan. Untuk mempergunakan kebolehan SC

yang memerangkap tenaga kinetik dan juga membekalkan tenaga cepatan dengan

berkesan pada BHEV, dua kaedah pengiraan kemuatan SC yang dipanggil sebagai

Reka bentuk Berasaskan Pencepatan (ABD) dan Reka bentuk Berasaskan

Nyahpecutan (DBD) diperkenalkan. Kaedah ini berasaskan pada prinsip pengekalan

tenaga yang mengimbangkan tenaga simpanan dalam SC dan tenaga kinetik

kenderaan, dan pada masa yang sama mengambil kira kehilangan semasa proses cas

dan nyahcas pada SC. Dari dua kaedah ini, dua strategi kawalan pengurusan tenaga

dibangunkan dan diguna pakai untuk BHEV. Pengaliran kuasa dan tenaga di antara

LB, SC dan beban penggerak dikawal melalui sistem kawalan gelung untuk arus SC;

isyarat rujukan untuk arus SC dijana berasaskan pada pendekatan ABD dan DBD.

Simulasi BHEV pada skala sebenar dilakukan menggunakan Matlab/SIMULINK

berasaskan kitar panduan Pencepatan maksimum dan kitar pemacuan bandar tambahan

(EUDC). Prestasi strategi yang dicadangkan ini dinilai dari segi pengurangan kuasa

puncak bateri, penambahbaikan perubahan voltan bateri, dan penggunaan tenaga

bateri. Akhir sekali, kaedah dicadang ini disahkan dari segi kesesuaian dan praktikal

melalui eksperimen skala kecil dan simulasi. Berdasarkan pada keputusan simulasi dan

eksperimen, didapati BHEV-DBD menghasilkan prestasi terbaik dari segi

pengurangan kuasa bateri, penambahbaikan perubahan voltan bateri dan penggunaan

tenaga bateri; berbanding dengan BEV konvensional, penambahbaikan diperolehi

masing-masing sehingga 46%, 3.5% dan 23%.

vii

TABLE OF CONTENTS

TITLE PAGE

DECLARATION ii

DEDICATION iii

ACKNOWLEDGMENTS iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS vi

LIST OF TABLES xi

LIST OF FIGURES xi

LIST OF ABBREVIATIONS xvii

LIST OF APPENDICES xx

CHAPTER 1 INTRODUCTION 1

1.1 Background 1

1.2 Issues related to Hybrid Energy Storage System 5

1.3 Problem Statement 7

1.4 Thesis Objectives 8

1.5 Scope of Work 9

1.6 Thesis Contributions 10

1.7 Thesis Organizations 11

CHAPTER 2 LITERATURE REVIEW OF ELECTRIC VEHICLE

AND ENERGY MANAGEMENT SYSTEMS 13

2.1 Introduction 13

2.2 Battery 15

2.3 Supercapacitor 20

viii

2.4 Battery and Supercapactior in Hybrid Energy Storage

System 22

2.5 Converter Topologies for Energy Source 25

2.6 Electric Vehicle Architectures 27

2.7 Modelling of Electric Vehicle 28

2.8 Energy Management Control Strategy 32

2.8.1 Rule-based Energy Management Control Strategy 33

2.8.1.1 Deterministic Rule-based Energy Management

Control Strategy 34

2.8.1.2 Fuzzy Rule-based Energy Management

Control Strategy 37

2.8.2 Optimization-based Energy Management

Control Strategy 39

2.8.2.1 Global Optimization Energy Management

Control Strategy 40

2.8.2.2 Real-time Energy Management Control Strategy 44

2.8.3 Summary of Energy Management Control Strategy 47

2.9 Chapter Conclusion 48

CHAPTER 3 ACCELERATION AND DECELERATION-BASED

DESIGN OF AUXILIARY ENERGY STORAGE FOR

BATTERY HYBRID ELECTRIC VEHICLE 49

3.1 Introduction 49

3.2 Acceleration-based Design and Deceleration-based Design

Strategies of Supercapacitor for Battery Hybrid Electric

Vehicle 49

3.2.1 Battery Hybrid Electric Vehicle 50

3.2.2 Acceleration-based Design 53

3.2.3 Deceleration-based Design 59

3.3 Control Strategy of Supercapacitor Current 61

ix

3.3.1 Current Control Strategy for Acceleration-based

Design 61

3.3.2 Current Control Strategy for Deceleration-based

Design 64

3.4 Current Control of Supercapacitor 66

3.4.1 Small Signal Modelling of Bi-directional

DC-DC converter 66

3.4.2 Supercapacitor Current Controller Design 74

3.5 Chapter Conclusion 76

CHAPTER 4 EXPERIMENTAL HARDWARE DESIGN AND

IMPLEMENTATION 77

4.1 Introduction 77

4.2 dSPACE DS1104 Controller Board and Implementation 77

4.2.1 Real-Time Interface Software 80

4.2.2 ControlDesk Developer Software 85

4.2.3 Three-phase PWM Signal Generator Block-set 87

4.3 Gate Driver Circuit 88

4.4 Power Bi-directional DC-DC Converter for Supercapacitor 89

4.5 DC Motor Drive System 91

4.6 Battery Bank 95

4.7 Supercapacitor Bank 96

4.8 Chapter Conclusion 98

x

CHAPTER 5 SIMULATION AND EXPERIMENTAL RESULTS 99

5.1 Introduction 99

5.2 Real-scale Simulation 99

5.2.1 Maximum Acceleration Driving Cycle Simulation 100

5.2.2 Extra Urban Driving Cycle Simulation 107

5.3 Small-scale Simulation and Experiment 113

5.3.1 Maximum Acceleration Driving Cycle Simulation

and Experiment 115

5.3.2 Extra Urban Driving Cycle Simulation and Experiment 124

5.4 Chapter Conclusion 131

CHAPTER 6 CONCLUSION AND FUTURE WORK 133

6.1 Conclusion 133

6.2 Future Work 135

REFERENCES 137

Appendices A – J 148-167

xi

LIST OF TABLES

TABLE NO. TITLE PAGE

Table 3.1 Characteristics of the BHEV based on PROTON SAGA FLEVE 51

Table 3.2 Specification of the SC bank of ABD and DBD 56

Table 3.3 PI parameters of the current controller for SC 75

Table 5.1 Simulation results of maximum acceleration driving cycle 107

Table 5.2 Simulation results of Extra Urban Driving Cycle 112

Table 5.3 Electric propulsion system parameters 113

Table 5.4 Experimental results of maximum acceleration driving cycle 123

Table 5.5 Experimental results of Extra Urban Driving Cycle 131

xii

LIST OF FIGURES

FIGURE NO. TITLE PAGE

Figure 1.1 Carbon dioxide emission by sector in 2009 2

Figure 1.2 Relative comparison of advantages and disadvantages of BEVs over

ICEVs 3

Figure 1.3 The significant performance of energy source/storage 4

Figure 1.4 Connection scheme of HESS (a) single converter scheme and (b)

multiple converters scheme 6

Figure 2.1 An EV system 13

Figure 2.2 Lithium-ion battery model in Matlab/SIMULINK 15

Figure 2.3 Web plot of the three principal lithium-ion battery technologies 16

Figure 2.4 Charge and discharge process of lithium-ion batteries 16

Figure 2.5 Charge-depleting micro cycle load profile 18

Figure 2.6 Battery cycle life versus working temperature 18

Figure 2.7 Battery end of life at different constant charging current rates 19

Figure 2.8 A basic material to make up a cylindrical SC 20

Figure 2.9 Simple equivalent circuit of SC 21

Figure 2.10 The structure of a cylindrical SC 22

Figure 2.11 Configurations of battery and SC HESS 24

Figure 2.12 Half-bridge converter connected to SC and battery 26

Figure 2.13 Possible configurations of EV system 28

Figure 2.14 Forces acting on a vehicle moving up a slope 29

Figure 2.15 The equivalent load torque model constructed using

Matlab/SIMULINK blocks. 32

xiii

Figure 2.16 Energy management control strategies studied for EV 33

Figure 3.1 PROTON SAGA Face Lift Electric Vehicle: (a) Picture of the SAGA

FLEVE, and (b) Architecture of the BHEV 50

Figure 3.1 Continued 51

Figure 3.2 Electrical and mechanical schematic diagram of BHEV 53

Figure 3.3 A series connection of SC six units implemented voltage management

circuitries 57

Figure 3.4 The 2 strings of SC connected in parallel for ABD and DBD 57

Figure 3.5 The Matlab/SIMULINK blocks for SC current reference generator of

ABD 63

Figure 3.6 The energy management control structure for BHEV with ABD 64

Figure 3.7 The Matlab/SIMULINK blocks of SC current reference generator for

DBD 65

Figure 3.8 PI controller structure for SC current control 66

Figure 3.9 Schematic diagram of the bi-directional DC-DC converter 67

Figure 3.10 Equivalent circuit model of boost converter; (a) circuit, (b) switch ON,

(c) switch OFF 70

Figure 3.11 Pole-zero map of transfer function of duty ratio to SC current 73

Figure 3.12 Bode plot duty ratio to SC current 74

Figure 3.13 Small signal transfer function of the duty ratio to SC current 74

Figure 3.14 Open loop response of the tuned current control loop 75

Figure 4.1 The picture of small-scale propulsion hardware for experiment 78

Figure 4.2 Schematic diagram of the experimental hardware 78

Figure 4.3 dSPACE DS1104 controller board; (a) picture of dSPACE DS1104

controller board, (b) architecture of the controller board 79

Figure 4.4 Real-Time Interface model of; (a) DC motor speed and current

control, and SC current control, and (b) energy and power monitoring

of the experiment 81

xiv

Figure 4.5 Real-Time Interface model of the SC voltage/current controller model

82

Figure 4.6 Real-Time Interface model for measuring power and energy of

battery, SC and DC motor 83

Figure 4.7 Signal measurements: (a) picture of the voltage and current

transducers, (b) picture of the interfacing board and, (c) Real-Time

Interface model of ADC ports 84

Figure 4.7 Continued 85

Figure 4.8 Window of ControlDesk developer plotters 86

Figure 4.9 3-phase PWM signal generator; (a) Real-Time Interface block-set, (b)

setup window 87

Figure 4.10 Gate driver circuit; (a) hardware picture, (b) schematic diagram 88

Figure 4.10 Continued 89

Figure 4.11 Power bi-directional DC-DC converter; (a) hardware picture, (b)

schematic diagram 90

Figure 4.12 DC motor separated field excited with flywheel inertial load 91

Figure 4.13 Graph of the run-out test of the DC motor in experiment 93

Figure 4.14 The IGBT module with a snubber capacitor for DC motor drive 94

Figure 4.15 Incremental speed encoder installed at the end of motor shaft 94

Figure 4.16 Sealed lead-acid battery bank 95

Figure 4.17 SC bank used in the experiment 97

Figure 5.1 Matlab/SIMULINK block diagram for real-scale simulation BHEV-

ABD and DBD 100

Figure 5.2 Vehicle speed profiles in maximum acceleration simulation 101

Figure 5.3 Reference and actual current of SC in maximum acceleration

simulation: (a) BHEV-ABD, and (c) BHEV-DBD 103

Figure 5.4 Battery’s power of all vehicles in maximum acceleration simulation

104

xv

Figure 5.5 Maximum acceleration simulation: (a) battery voltage, and (b)

currents of battery, converter, and drive 105

Figure 5.6 Battery’s energy consumption of all vehicles in maximum acceleration

simulation 106

Figure 5.7 Vehicle speed profiles in EUDC simulation 107

Figure 5.8 Reference and actual current of SC in EUDC simulation: (a) BHEV-

ABD, and (b) BHEV-DBD 109

Figure 5.9 Battery’s power of all vehicles in EUDC simulation 110

Figure 5.10 EUDC simulation: (a) battery voltage, and (b) battery current 111

Figure 5.11 Battery’s energy consumption of all vehicles in EUDC simulation 112

Figure 5.12 Vehicle speed profiles in maximum acceleration: (a) Simulation and

(b) Experiment 116

Figure 5.13 Reference and actual current of SC in maximum acceleration

simulation and experiment: (a) BSCS-ABD and (b) BSCE-ABD 117

Figure 5.14 Reference and actual current of SC in maximum acceleration

simulation and experiment: (a) BSCS-DBD and (b) BSCE-DBD 118

Figure 5.15 Battery’s power profiles of maximum acceleration: (a) Simulation and

(b) Experiment 119

Figure 5.16 Small-scale maximum acceleration: (a) battery voltage in simulation,

(b) battery voltage in experiment, (c) battery current in simulation, and

(d) battery current in experiment 120

Figure 5.16 Continued 121

Figure 5.17 Battery’s energy consumption of maximum acceleration: (a)

Simulation and (b) Experiment 123

Figure 5.18 Vehicle speed profiles in EUDC: (a) Simulation and (b) Experiment

124

Figure 5.19 Reference and actual current of SC in EUDC simulation and

experiment: (a) BSCS-ABD and (b) BSCE-ABD 125

xvi

Figure 5.20 Reference and actual current of SC in EUDC simulation and

experiment: (a) BSCS-DBD and (b) BSCE-DBD 126

Figure 5.21 Battery’s power profiles of EUDC: (a) Simulation and (b) Experiment

127

Figure 5.22 Small-scale EUDC: (a) battery voltage in simulation, (b) battery

voltage in experiment, (c) battery current in simulation, and (d) battery

current in experiment. 128

Figure 5.22 Continued 129

Figure 5.23 Battery’s energy consumption of EUDC: (a) Simulation and (b)

Experiment 130

xvii

LIST OF ABBREVIATIONS

a - Vehicle acceleration rate

Af - Frontal vehicle area of vehicle

Bm - Viscous friction coefficient of motor

Cd - Aerodynamic drag coefficient

C - Output capacitance of converter

CSC,cell - Capacitance of a single supercapacitor cell

CSC - Actual SC capacitance

�̃�(s) - Duty ratio in s-domain

d - Vehicle deceleration rate

EB - Battery energy consumption

Far - Aerodynamic resistance force

Fgr - Grading resistance force

Frr - Rolling resistance force

Fte - tractive effort

Ftr - Tractive resistance force

g - Gravity acceleration rate

G - Overall gear ratio

𝑖𝑆𝐶(𝑠) - SC current in s-domain

𝑖𝑆𝐶(𝑡) - Time-varying SC current

𝑖𝑆𝐶,𝑟𝑒𝑓(𝑡) - Time-varying SC current reference

ISC,max - Maximum current of supercapacitor

Jeq - Equivalent moment of inertia of the motor

Jm - Equivalent moment of inertia of motor and flywheel

L - Converter inductance

La - Armature inductance

MSC - Supercapacitors mass

MV - Vehicle mass

Np - Number of parallel connection

Ns - Number of series connection

xviii

𝑃𝑖(𝑡) - Time-varying input power of motor

�́�𝑙(𝑡) - Time-varying load power

Pbat - Battery power

Pi - Input power of the motor

Pdr - Driving power

Pdy - Dynamic power

PSC,max - Maximum power of supercapacitor

Ptr - Tractive load power

rC - Internal resistance of output capacitor

rSC - Internal resistance of SC

rSC,cell - Internal resistance of a single cell of SC

rL - Equivalent inductive resistance of converter

rwh - Wheel diameter of vehicle

R - Equivalent resistance at maximum power

Ra - Armature resistance

Tdy - Dynamic load torque

Teq - Equivalent load torque transferred through the single gear

ratio

Twh - Load torque at wheel of the vehicle

𝑢𝑆𝐶(𝑡) - Time-varying internal voltage of SC

𝑢𝑆𝐶𝑠,𝑟𝑒𝑓(𝑡) - Time-varying internal voltage reference of SC

𝑣𝑆𝐶(t) - Time-varying terminal voltage of SC

𝑠𝑉,𝑟𝑒𝑓(𝑡) - Time-varying vehicle speed reference

𝑠𝑉(𝑡) - Time-varying vehicle speed

sV,max - Maximum speed of vehicle

sV,ref - Reference speed of vehicle

VB - Battery voltage regulation

μrr - Rolling resistance coefficient

ρ - Air density

α - Road grading angle

ηcon - Average efficiency of converter

ηinv - Average efficiency of inverter

xix

ηm - Average efficiency of motor drive system

ηmech - Average efficiency of mechanical system

ηSC - Average efficiency of SC

ηtotal - Total efficiency

⍵(𝑡) - Time-varying angular speed of motor

ωm - Angular velocity of the motor

ωm,max - Maximum angular speed of motor

xx

LIST OF APPENDICES

APPENDIX TITLE PAGE

Appendix A MATLAB Coding for Duty Ratio to SC Current

Transfer Function of DBD

148

Appendix B Control Strategy Derivations 150

Appendix C Specification of IGBT 151

Appendix D Specification of Incremental Speed Encoder 152

Appendix E Specification of Sealed Lead-acid Battery 154

Appendix F Specification of Supercapacitor 156

Appendix G Design and Development of Saga FLEVE for Proton

Green Mobility Challenge 2012

158

Appendix H

Real-scale Vehicle Simulation of BEV and BHEVs

with UDDS

163

Appendix I Small-scale Simulation for Battery Energy

Consumption using the Real-scale Internal Resistance

of SC and Inductor

165

Appendix J List of Publications 166

1

CHAPTER 1

INTRODUCTION

1.1 Background

World energy resources are developed from the plant and animal remainings

in the earth’s shell, which dwelled millions of years ago, known as the fossil energies.

Coal, petroleum, and natural gas are the major forms of the fossil fuels constituting the

world’s majority energy resources. During the oil crisis in 1973, people became

attentive to the fact that fossil energies are the valuable product of the earth. For the

last twenty years, the Brent crude oil price on the US market has increased from $17.85

per barrel in January 1996 to the peak at $132.72 in June 2008 and fluctuated between

$50- 125 ever since [1]. Consequently, the governments and the industries globally,

have committed to continuously improve energy economy for all activities:

production, distribution and consumption.

In the report of energy consumption by sector in 2009, the energy consumed

by the transportation holds the second rank of the primary energy consumption and

carbon dioxide emission [2] as shown in Figure 1.1. The carbon dioxide dominates the

greenhouse gas emission, and it contributes to the global warming which affects the

whole life on earth. Greenhouse gases are not only composed of the carbon dioxide

but also other harmful gases such as carbon monoxide, unburned hydrocarbons,

nitrogen oxide, sulphur and methane which generate lots of induced costs; for example,

health expenses, the cost of replanting forests devastated by acid rain, and the cost of

cleaning and fixing surfaces corroded by acid rain. In fact, the induced costs are

difficult to assess, and they may include the cost of the damages caused by hurricanes,

lost crops due to dryness, damaged properties due to floods, and international aid to

2

relieve the affected populations [3]. In this research, the focus in improving the energy

efficiency of the transportation sector, particularly the battery electric vehicle (BEV).

Specifically, the aim is to reduce the energy consumption and to improve the

performance of energy storage system (ESS).

Figure 1.1 Carbon dioxide emission by sector in 2009 [2]

BEVs are vehicles energized by electricity stored in batteries. They offer

significant potential in reducing the consumption of petroleum products and reduces

the generation of greenhouse gases. The first BEV was launched in the 1830s and

commercially traded at the end of the 19th century, but the best time of the electric-

powered vehicle was short-lived. By that time, it was recognized that BEV has high

running cost and poor performance including short driving range, took long charging

period, and short driving durability even in the city. Meanwhile, the internal

combustion engine vehicle (ICEV), discovered in 1860, received an abundant attention

due to cheap fuel, rapid technology revolution, and reliable assembly production. As

a result, the development of BEV was virtually ceased by the early 1930s [3].

However, BEV was reborn as the foregoing reasons during the latter part of the 20th

century where they have been technically advanced in design, battery performance,

traction motors and inverters [4]. The advantages/disadvantages of BEVs are

relatively compared with ICEV as shown in Figure 1.2, in which 0, 1, 2, 3, 4, 5 denotes

much worse, worse, similar, better, much better and best, respectively [3].

Residential, commercial, and industry

26%

Transportation34%

Electric power40%

3

Figure 1.2 Relative comparison of advantages and disadvantages of BEVs over

ICEVs [3]

BEVs are the next generation of vehicles after ICEVs and hybrid electric

vehicles (HEVs). Figure 1.3 illustrates the significant performance of battery energy

and power density for various battery types (e.g., nickel cadmium, lead acid battery

and lithium-based battery (LB). As LB offers the highest rating, it is feasible to use

LB as the main energy storage in BEVs. Neubauer et al. [5] reported that, in order to

compete with the ICEV, the battery of BEVs needs to have a specific power of at least

470 W/kg and specific energy of 235 Wh/kg. In addition, BEV drivers require driving

in a range of about 20,000 km per year. Consequently, 10+ years of vehicle life and a

payback period of 5 years are expected. For a typical driving range of 50 km, a vehicle

usually consumes about 2,700 Wh of energy. Thus to travel for 500 km, about 100 kg

of LB bank is required, which is equivalent to the energy of one tank of petrol [6], [7].

0

1

2

3

4

5

Reducedemissions

Quietness

Overallefficiency

Power/weightratio

Driveability

Smoothness

Refuelling

Durability

BEVs

4

Figure 1.3 The significant performance of energy source/storage [8], [9]

Nowadays, the demand in high specific power and high specific energy is

partially fulfilled by the advancement in LB technology, in which a specific energy of

around 400 Wh/kg, and the specific power of approximately 500 W/kg can be achieved

(as shown in Figure 1.3). However the extremely high power requirements during

acceleration and deceleration whereby the battery needs to supply very large power to

the propulsion load and need to absorb enormous amount of regenerative braking

energy can cause problems to LB in BEV [10], [11]. Under these extreme operating

conditions, the battery’s internal resistance increases due to the increase in

temperature, thus decreases the energy efficiency and the lifecycle of the battery [12],

[13], [14]. The LB used in the simulation work of this thesis has the maximum

discharge current limit up to 7.5 times (600 A) of the standard charging current (C),

80 A, for supplying acceleration power. However, it has the maximum charging ability

of only 2C for recapturing energy from regenerative braking as shown in Appendix G.

Thus, the energy from deceleration cannot be recovered 100%. The energy is then

dissolved by means of friction using mechanical braking, in general. The mechanical

braking does not only cause of the heat dissipation but also diffuse hazard particles to

the surrounding environment that affect the people and the vehicle parts and

components themselves. The heat source in a BEV can also come from the battery

that supplies and receives high peak power to and from the propulsion load

respectively. The high temperature of the battery requires good heat ventilation system

to maintain its operation, otherwise, the internal resistance can increase rapidly [14].

SC

5

To solve these problems, energy management system, which is widely used in

many industrial firms for improving energy performance, is implemented. The aim of

energy management system is to establish an efficient system and necessary steps to

improve energy performance. This method can be applied to all kinds of energy

consumption units [15]. Lately, surge of interest in the applications of energy

management system to BEV can be seen; by proposing hybrid energy storage system

(HESS) between LB and supercapacitor (SC) [16], [17], [18], [19], [20], [21], [22].

These studies presented the advantages of HESS in terms of power and energy

availability, battery life extension, lower battery temperature, lower energy loss,

economical implementation, etc. The other type of HESS used in BEV is a

combination of battery and a mechanical flywheel [23], [24]. However, the

implementation of a flywheel as energy storage is not only complex and inefficient,

but also is not safe [25]. Therefore, currently, the HESS consisting of LB and SC is

generally accepted as the most suitable and safest solution for BHEV applications

[26], [24], [27], [28].

SC is an electrochemical double layer capacitor having high specific area of

activated porous carbon to contain a large amount of electric [29]. It has a low specific

energy density in the vicinity of 5Wh/kg but possesses a high specific power around

10 kW/kg [30]. Compared to LB, the specific energy density of SC is lower; however,

it has much higher specific power density. The outstanding performance of SC is the

extremely long life cycle, which is about one million cycles [31]. It is anticipated that

the application of LB and SC in HESS for BEV, which is called battery hybrid electric

vehicle (BHEV), will become an ultimate solution for solving the deteriorated battery

problem found in BEV, thus, enhancing the vehicle performance.

1.2 Issues related to Hybrid Energy Storage System

There are two primary concerns related to the energy management system for

BHEV using SC: first is the configuration schemes used for the HESS and, second is

the energy management control strategy between the energy storages. The first issue

has been studied by many researchers, and in general, two types of configurations

6

have been proposed: a single bidirectional DC-DC converter connecting to either SC

or battery [32], [11], [33], [34], [35] and multiple bi-directional DC-DC converters

connecting to SC and battery [34], [36], [37], [22], as shown in Figure 1.4. A single

converter connected to the SC allows variation in the DC bus voltage according to the

state of charge (SOC) of the battery, while with multiple converter schemes the DC

bus voltage is basically fixed. If the DC bus voltage is to be fixed using a DC-DC

converter, losses caused by the converter used for the battery has to be considered.

The configuration scheme used in this study considers the presently available

technology in which the DC bus voltage (i.e. input to the propulsion inverter) is

allowed to vary from the maximum to half of the rated voltage [38]. The trade-off

between the loss in a converter for maintaining DC bus voltage and the loss of

propulsion inverter fed by the high voltage variation (direct connection of the battery

to the inverter) can be considered equal since they are both controlling the same

amount of power between the battery and the propulsion load. Furthermore, a single

converter scheme is more reliable than that of multiple converters configuration. For

instance, a vehicle can become inoperative if one of the converters in the multiple

converter scheme is broken.

Figure 1.4 Connection scheme of HESS (a) single converter scheme and (b)

multiple converter scheme

The second concern related to the energy management system is the energy

management control strategy, which can be categorized into two approaches, i.e. rule-

based energy management control strategy and optimization-based energy

management control strategy. Zhang et al. [39] have analysed the energy management

control strategy for BHEVs and found that rule-based energy management control

strategy is an exclusive strategy and can be commercially implemented. Although it

is computationally efficient and easy to implement, optimal solution is however not

7

guaranteed. On the other hand, the optimization-based energy management control

strategy, which finds solution optimally, has been widely studied, however very

difficult or almost impossible to be implemented in real-time driving environment.

With the aim of obtaining a practical and optimal energy management control strategy

for BHEVs, currently the researchers are focusing on developing optimum rule-based

energy management control strategies and reducing the computational burden during

optimization processes. At the moment, these techniques are still in the developing

stages and are not yet used in BHEVs. In this thesis, energy management control

strategy based on deterministic (heuristic) rule-based control strategy is chosen. In

developing this strategy, human expertise, engineering intuition and powertrain

characteristics are exploited. The deterministic rule-based energy management

control strategy is suitable for the real-time control implementation for BHEV since

it requires less demanding computational requirement and easy to implement. The

advantages and disadvantages of rule-based and optimization-based energy

management control strategy are discussed in Chapter 2. From this point of view, a

new control strategy based on deterministic rule-based energy management control

strategy is considered in this thesis.

1.3 Problem Statement

The main problem associated with deterministic rule-based energy

management control strategy for BHEV using single converter scheme, as presented

in literature, is in the real-time generation of the correct SC current reference. An

extreme (too high) SC current reference generated by a controller can cause a full

discharge of SC stored energy before the end of an acceleration is reached. In contrast,

a too low reference resulted in an ineffective utilization the stored energy in the SC.

In order to maximize the utilization of the SC in BHEV, not only the current has to be

controlled properly, but at the same time a suitable capacitance value of the SC has to

be determined analytically. Inappropriate determination of the capacitance may

underutilize (or over-utilize) the SC thus render ineffective operation of the proposed

rule-based energy management control strategies.

8

1.4 Thesis Objectives

The work in this thesis proposes two new methods of SC capacity calculations

and hence two deterministic rule-based energy management control strategies for

HESS of a BHEV. The hybridised energy storage between LB and SC is based on a

single converter scheme. The two methods are named as acceleration-based design

(ABD) and deceleration-based design (DBD). The former calculates the SC capacity

by using the principle of conservation of energy that balances the vehicle kinetic

energy with the stored energy in the SC during acceleration, taking into account the

discharge losses. The latter calculates the capacity of the SC based on the balanced

energy during braking (deceleration), taking into account SC charging losses. The

proposed energy management control strategies generate the SC reference currents

using ABD and DBD approaches, from the v-i relationship of a capacitor that is

obtained from energy conservation law of vehicle kinetic energy and SC stored energy.

In these strategies, the SC is used to assist the main energy storage (i.e. the battery) in

supplying the energy and power to the propulsion load. The control performances of

the proposed techniques are simulated and experimented as presented in Chapter 5.

The improvements are demonstrated in terms of battery peak power reduction, DC bus

voltage variation reduction, and a better energy saving compared. The specific

objectives of this research are listed as follows:

(i) To formulate the capacity of SC auxiliary energy storage based on

ABD and DBD to obtain the best performance of HESS. This is

achieved by using the principle of conservation of energy during

acceleration or deceleration.

(ii) To design and develop two new control strategies to control the SC

current based on acceleration and deceleration of the vehicle, taking

into account the charging and discharging losses of the SC.

(iii) To model, design and simulate a real-scale BHEV using

Matlab/SIMULINK . The controllers are to be designed based on the

9

averaged and linearised model of the system, while the verification

is to be based on a large-signal model of the system, consisting of

the battery, SC, bi-directional DC-DC converter and motor drive

system connected to the vehicle propulsion load.

(iv) To develop and build a small-scale (laboratory-scale) inertial

propulsion system to study on the feasibility, effectiveness and

practicability of the proposed control strategies. Experimental

results are to be compared with the results obtain from the simulation

of the small-scale model.

1.5 Scopes of Work

The modelling, design, simulations and experiments conducted in this thesis

are confined within the following scopes:

(i) The energy management control strategies for BHEV developed in this

thesis is designed for a typical subcompact car (B-segment). Nonetheless,

applications to other class of cars or vehicles can be readily applied with

minor changes.

(ii) Modelling and simulation work conducted for the real-scale and small-

scale are performed using Matlab/SIMULINK with standard toolboxes.

These include the controller design using the averaged and linearized

models, as well as the large-signal simulation model for controller

verifications.

(iii) The controllers for small-scale experiments are developed using DS1104

controller board from dSPACE. The C-codes are generated using Rapid

Control Prototyping (RCP) technique and monitored and recorded using

ControlDesk software from dSPACE.

10

(iv) Due to the hardware and equipment constraints, verifications of the

proposed strategies in terms of feasibility and practicability is performed

using small-scale experimental set-up. However, due to the relatively

much smaller amount of energy involved compared to the actual scale,

losses in the converters of the small-scale system becomes significant.

These limitations are discussed in Chapter 5 of the thesis.

(v) Three different duty cycles are used to test and analyze the effectiveness

of the proposed strategies: maximum acceleration driving cycle, Extra

Urban Driving Cycle (EUDC) and Urban Dynamometer Driving

Schedule (UDDS). The actual-scale simulation results for the UDDS are

presented in Appendix H.

1.6 Thesis Contributions

This research contributes to the determination of proper capacity of the SC and

its respective energy management control strategies, known as ABD and DBD. The

contributions of the thesis are summarized as follows:

(i) The development of two novel techniques in calculating the capacity of

the SC that include the charging and discharging losses. Determining the

suitable capacitance for the SC is important to ensure that the SC is not

under-utilized (or over-utilized) that can result in inefficient energy

management control.

(ii) The design and development of two novel deterministic rule-based

energy management control strategies for controlling the SC current in

BHEV. The complexity in the modelling and generating the SC reference

current is removed by using a simplified v-i model of the SC. The

improvements in terms of battery peak power reduction, battery voltage

11

variation reduction, and battery energy consumption reduction are

achieved and presented.

(iii) The construction of averaged and linearized model of the system for

controller design and development of complete large-signal model of the

system for controller performance verifications.

(iv) The development and construction of the small-scale experimental set-

up which is equivalent to the simulated actual-scale of BHEV. The small-

scale experiments are conducted mainly to study on the feasibility and

practicability of the proposed control strategies.

1.7 Thesis Organizations

This thesis is organized into six chapters. Their contents are described as

follows:

(i) Chapter 1 delivers a brief introduction to the study. It covers the

background, thesis objectives, problem statement and scope of the work,

thesis contributions, and thesis organisations.

(ii) Chapter 2 reviews electric vehicle and energy management systems and

electric vehicle architectures. The modelling of an electric vehicle,

battery and SC hybrid energy storage systems and converter topologies

for an energy sources are also presented. Finally, overview on the

previous energy management control strategies are presented.

(iii) Chapter 3 explains the acceleration-based design and deceleration-based

design of the energy management control strategies for BHEV. In this

chapter, the description of the BHEV, acceleration-based design strategy,

deceleration-based design strategy, and current control of the SC are

presented.

12

(iv) Chapter 4 presents hardware design and development. The experimental

setup of the small-scale inertial propulsion system for hybrid energy

storage between battery and SC is described. The descriptions on the

dSPACE DS1104 controller board, gate driver circuit, power bi-

directional DC-DC converter, 2-quadrant DC motor drive system, battery

bank and SC bank are also given in details.

(v) Chapter 5 reports the simulation results (for small-scale and actual-scale)

and experimental results (for small-scale) of the proposed control

strategies in terms of battery peak power reduction, battery voltage

variation reduction, and battery energy consumption reduction. Results

are presented, discussed and compared.

(vi) Chapter 6 summarises the work in this thesis and highlights the

contributions of this research. Several suggestions are provided for

possible directions of future work.