gps-based optimization of phev power demands in a cold weather city

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GPS-based Optimization of PHEV Power Demands in a Cold Weather City Ryan Smith; Matthew Morison; David Capelle; Caleigh Christie; Danny Blair, Ph.D. University of Winnipeg’s Department of Geography

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GPS-based Optimization of PHEV Power Demands in a Cold Weather City. Ryan Smith; Matthew Morison; David Capelle ; Caleigh Christie ; Danny Blair, Ph.D. University of Winnipeg’s Department of Geography. Introduction. What is a PHEV?. http://www.eeh.ee.ethz.ch/. Introduction. - PowerPoint PPT Presentation

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Page 1: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

GPS-based Optimization of PHEV Power Demands in a Cold

Weather City

Ryan Smith; Matthew Morison; David Capelle; Caleigh Christie; Danny Blair, Ph.D.

University of Winnipeg’s Department of Geography

Page 2: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Introduction

http://www.eeh.ee.ethz.ch/

What is a PHEV?

Page 3: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Introduction

• Power Requirements depend on Distance, Speed, Acceleration and Duration

• Time available for Battery Recharging

• Opportunity (daytime) charging

• At-home (evening) charging

How do you design a PHEV?

Page 4: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Purpose

• Modeling power demands of PHEVs under a variety of temperature and recharging scenarios to understand the environmental and economic benefits of PHEV use

• Using a duty cycle previously created from a real-time GPS-based dataset collected by the University of Winnipeg’s AUTO21 research team (Smith et al., 2011)

Page 5: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Vehicle Power Demand – the Duty Cycle

• A representative, 24-hour profile• Duty Cycles indicate:

– Typical speed and acceleration demands– Hours of the day vehicle is in operation– Number of Trips / Day– Time available for Recharging

• Derived: Multiple vehicles, thousands of trips over long periods of time

Page 6: GPS-based Optimization of PHEV Power Demands in a Cold Weather City
Page 7: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Participants• Seventy-six volunteer drivers collecting

GPS data while driving, from Winnipeg & nearby communities.

• One year period• Recruitment:

– Local media– Word-of mouth – Sample bias towards higher-income

households… a good thing?

Page 8: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Equipment

• 76 GPS receivers (Otto Driving Companion)– Store 300 hours of data @ one-second intervals– Plug-in to vehicle lighter socket– Transfer data to PC via USB cable

• Accuracy:– Position: 10 metres– Speed: 1 km/h

myottomate.com/checkoutotto.asp

Page 9: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

WPG03 Duty Cycle

Page 10: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Modeling PHEV Power Demands

• 3 different types of PHEVs• 4 temperatures• 2 charging scenarios

Page 11: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Governing Equations

WPG03

VariedInputs

Page 12: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Go to…Power Demand Model

Page 13: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Results

Page 14: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Table 8: modeled gasoline and electricity demands of various PHEV models with overnight charging only using the WPG03PHEVx Ambient

Temperature (°C)

Electric range (km)

Gasoline range (km)

Electricity (DC)

(kWh)

Gas consumed

(L)

Fuel Economy

(L/100 km)

Electricity consumption

(Wh/km)

Electricty (AC)

(kWh)

Cost of charge (CAD)

(6.5¢/kWh)

Cost of gasoline (CAD)

(96¢/L)

Annual cost (CAD)

(240

cycles)CV 0 0.0 25.4 0.0 3.8 14.9 0.0 0.0 0.0 3.6 866.9

PHEV5 15 7.9 17.4 1.4 2.7 10.8 55.3 1.8 0.1 2.6 659.2PHEV5 0 7.6 17.7 1.4 2.8 10.9 55.3 1.8 0.1 2.6 661.3PHEV5 -15 8.1 17.2 1.4 2.7 10.9 55.3 1.8 0.1 2.6 660.5PHEV5 -30 7.2 18.1 1.4 2.7 10.8 55.3 1.8 0.1 2.6 658.7

PHEV10 15 16.1 9.3 2.8 1.7 6.8 111.5 3.5 0.2 1.6 449.1PHEV10 0 17.2 8.2 2.8 1.7 6.8 111.7 3.5 0.2 1.6 450.2PHEV10 -15 17.1 8.2 2.8 1.7 6.8 111.4 3.5 0.2 1.6 448.9PHEV 10 -30 15.9 9.4 2.8 1.7 6.8 111.4 3.5 0.2 1.6 448.9

PHEV20 15 24.7 0.6 4.7 0.4 1.5 183.6 5.8 0.4 0.4 176.4PHEV20 0 22.9 2.4 4.2 0.7 2.9 165.2 5.2 0.3 0.7 253.1PHEV20 -15 20.8 4.5 3.7 1.1 4.5 146.8 4.7 0.3 1.1 333.8PHEV20 -30 17.5 7.8 3.3 1.5 6.0 128.3 4.1 0.3 1.5 412.0

Cost Comparison for Overnight Charging Only

Page 15: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Table 9: modeled gasoline and electricity demands of various PHEV models with overnight charging and 3.5 hours opportunity charging using the WPG03PHEVx Ambient

Temperature (°C)

Electric range (km)

Gasoline range (km)

Electricity (DC)

(kWh)

Gas consumed

(L)

Fuel Economy

(L/100 km)

Electricity consumption

(Wh/km)

Electricty (AC)

(kWh)

Cost of charge (CAD)

(6.5¢/kWh)

Cost of gasoline

(CAD) (96¢/L)

Annual cost (CAD)

(240

cycles)PHEV5 15 16.9 8.4 2.8 1.6 6.4 110.7 3.5 0.2 1.6 430.1PHEV5 0 17.3 8.0 2.8 1.6 6.4 110.7 3.5 0.2 1.6 430.4PHEV5 -15 16.8 8.4 2.7 1.7 6.6 108.2 3.4 0.2 1.6 440.5PHEV5 -30 15.0 10.3 2.6 1.8 7.0 103.4 3.3 0.2 1.7 459.4

PHEV10 15 24.5 0.8 4.4 0.4 1.5 175.1 5.6 0.4 0.4 176.2PHEV10 0 22.7 2.5 4.0 0.7 2.8 159.2 5.1 0.3 0.7 243.3PHEV10 -15 20.4 4.9 3.6 1.1 4.3 141.0 4.5 0.3 1.0 321.7PHEV 10 -30 17.0 8.3 3.1 1.5 5.9 122.1 3.9 0.3 1.4 402.5

PHEV20 15 24.7 0.6 4.7 0.4 1.5 183.6 5.8 0.4 0.4 176.4PHEV20 0 22.9 2.4 4.2 0.7 2.9 165.2 5.2 0.3 0.7 253.1PHEV20 -15 20.8 4.5 3.7 1.1 4.5 146.8 4.7 0.3 1.1 333.8PHEV20 -30 17.5 7.8 3.3 1.5 6.0 128.3 4.1 0.3 1.5 412.0

Cost Comparison for Opportunity and Overnight Charging

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Page 16: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Conclusion• Cold temperatures affect vehicle operation

energy costs• Daytime opportunity charging dramatically

reduces energy costs• Large battery PHEVs (PHEV20) are not

optimal for the WPG03 • From engineering and consumer points of

view, optimization (on a per duty cycle basis) is necessary to realize the full environmental and economic benefits of PHEV technology.• Goldilocks effect

Page 17: GPS-based Optimization of PHEV Power Demands in a Cold Weather City

Acknowledgments

• Frank Franczyk, Persen Technologies Inc.• Department of Geography, University of Winnipeg

Funding and Support