Impact of Driving Behavior on PHEV Fuel Consumption for … · 2010-07-09 · 2009 DOE Hydrogen Program and Vehicle Technologies . Annual Merit Review . June 08, 2010. Aymeric Rousseau

Impact of Driving Behavior on PHEV Fuel Consumption for Different Powertrain,

Component Sizes and Control

2009 DOE Hydrogen Program and Vehicle Technologies Annual Merit Review

June 08, 2010

Aymeric Rousseau (PI)Argonne National Laboratory

Sponsored by Lee Slezak

This presentation does not contain any proprietary, confidential, or otherwise restricted information

Project ID #VSS011

Project OverviewTimeline

Start – September 2009

End – September 2010

90% Complete

Budget FY09 - $200K

FY10 - $250K

Barriers Evaluate fuel displacement potential in

real world driving conditions

Partners U.S. EPA

City of Chicago

University of California Davis

MathWorks

2

Objectives

Define the best control strategy philosophy for different battery characteristics

Select the most appropriate set of control parameters to maximize fuel efficiency while maintaining acceptable drive quality and maximizing battery life

Define the most appropriate battery energy/power to maximize fuel displacement

Assess the impact of driving distance and driver aggressiveness on fuel displacement

3

Milestones

4

Q1 Q2 Q3

Drive Cycle Implementation

Control Strategy Selection

Component Sizing Impact

Distance Impact

Driver Aggressiveness Impact

Current Status

Q4

Report

Approach

0 200 400 600 800 1000 12000

5

10

15

20

25

Time (s)

Spee

d (m

ph)

Drive cycle

0 500 1000 1500 2000 2500 30000

5

10

15

20

25

30

35

40

Time (s)

Spee

d (m

ph)

Drive cycle

0 500 1000 1500 2000 25000

5

10

15

20

25

30

35

Time (s)

Spee

d (m

ph)

Drive cycle

Real World Drive Cycles

>110 TripsOne day in Kansas City

Battery Power

Engine Power

Battery Energy

Convergence

Yes

No

Motor Power for Cycle

Vehicle Assumptions

AutomatedSizing

Midsize Vehicle

Analysis(Distribution)

0

2

4

6

8

10

Num

ber o

f occ

uren

ces

(%)

0 50 100 150 200 250 3000

10

20

30

40

50

60

70

80

90

100

Cum

ulat

ive

pow

er (%

)

Pess (kW)

Mean=115kW

Median=100kW

Std=48kW

Number of trips=111

Distribution of Pess max discharging for each trip

0

2

4

6

8

10

Num

ber o

f occ

uren

ces

(%)

0 50 100 150 200 250 3000

10

20

30

40

50

60

70

80

90

100

Cum

ulat

ive

pow

er (%

)

Pess (kW)

Mean=123kW

Median=107kW

Std=54kW

Number of trips=111

Distribution of Pess sized for each trip

0

4

8

12

16

20

Nu

mb

er o

f o

ccu

ren

ces

(%)

-90 -80 -70 -60 -50 -40 -30 -20 -10 00

10

20

30

40

50

60

70

80

90

100

cum

ula

tive

po

wer

(%

)

Pess (kW)

Mean=-32kW

Std=12

Number of cycles=290

Distribution of Pess max charging for each cycle

5

Technical AccomplishmentsSelection of Control Strategies – Fuel Consumption

0 1 2 3 4 5 60

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Fuel Consumption [liter/100km]

Den

sity

[-]

Split 4kWh LoadEngPwr 10mi CD rangeSplit 4kWh OnlyOptEngPwrSplit 4kWh DiffEngPwr max P thresholdSplit 4kWh DiffEngPwr 10mi CD rangeSplit 4kWh DiffEngPwr 20mi CD range

Example of Power Split HEV with 4kWh Total Energy

6

The Load Engine Power and Differential Engine Power 20mi demonstrate the lowest fuel consumption

Technical AccomplishmentsSelection of Control Strategies – Drive Quality, Battery Life

-0.5 0 0.5 1 1.5 2 2.5 30

0.5

1

1.5

Number of starts per distance [#starts/mile]

Den

sity

[-]


0 10 20 30 40 50 60 70 80 900

0.02

0.04

0.06

0.08

0.1

0.12

battery rms current [Amps]

Den

sity

[-]


7

The Differential Engine Power tuned for 20 miles AER on the UDDS clearly provides lower battery RMS current

Several controls provide low number of engine starts, including the Optimum Engine Power and the Differential Engine Power

Technical AccomplishmentsComponent Sizing Has Clear Impact on Fuel and Electrical Consumption Patterns

8

HEV Split PHEV 4kWh

Split PHEV 8kWh Series PHEV 12kWh

Technical AccomplishmentsImpact of Distance on Fuel Consumption Displacement

9

5.5 6 6.5 7 7.5 8 8.50

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2


Den

sity

[-]

2.5 3 3.5 4 4.5 5 5.5 6 6.5 70

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9


Den

sity

[-]

0-30 miles30-60 miles60-90 miles


Conventional

Power Split HEV

The driving distance has a small influence on the conventional (STD from 0.2 to 0.35). The impact increases slightly for the HEV (STD from 0.38 to 0.55)

STD = standard deviation


10

0 1 2 3 4 5 6Fuel Consumption [liter/100km]


0

0.5

1

1.5

2

2.5

Den

sity

[-]

5-2 -1 0 1 2 3 4



0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Den

sity

[-]

The driving distance impact increases with the available electrical energy (STD from 0.6 to 0.7 for the 8kWh and 0.1 to 0.8 for the 12kWh)

Power Split PHEV 8kWh

Series PHEV 12 kWh

STD = standard deviation

TO

CO

NV

ENT

ION

AL

Vehicle 0-30 miles 30-60 miles 60-90miles

Conventional 0.0% 0.0% 0.0%HEV 2.7% 2.6% -0.2%

Split 4kWh 19.7% 25.8% 6.1%Split 8kWh 27.6% 40.4% 12.8%

Series 12kWh 21.1% 42.2% 21.1%Series 16kWh 9.7% 33.7% 24.0%

TO

H

EV

Vehicle 0-30 miles 30-60 miles 60-90miles

Conventional -2.7% -2.6% 0.2%HEV 0.0% 0.0% 0.0%

Split 4kWh 25.5% 34.1% 8.6%Split 8kWh 37.6% 55.5% 17.9%

Series 12kWh 29.2% 58.6% 29.4%Series 16kWh 13.4% 46.8% 33.4%


Percentage of Fuel Saved as a Function of Distance

11

0 10 20 30 40 50 60 70 80 900

10

20

30

40

50

60

70

80

90

100

Distance (mile)

Fuel

Sav

ed (%

)

HEV Compared to Conventional

Slow speedMedium speedFast speedShort distanceMedium distanceLong distanceLow aggressivenessMedium aggressivenessHigh aggressiveness

Technical AccomplishmentsImpact of Driver Aggressiveness

12

- Spread of ~20% independent of distance- Benefits decreased with increased average speed

0 10 20 30 40 50 60 70 80 900

10

20

30

40

50

60

70

80

90

100

Distance (mile)

Fuel

Sav

ed (%

)

Blended PHEV (8kWh) Compared to Conventional



13

Benefits depend on distance

0 10 20 30 40 50 60 70 80 900

10

20

30

40

50

60

70

80

90

100

Distance (mile)

Fuel

Sav

ed (%

)

Series PHEV (16kWh) Compared to Conventional



14

Most cycles up to 40 miles can be run in EV mode (16kWh total, 60% usable, minimum accessory loads)

15

PHEV Model in Autonomie

Fuel Consumption onReal-World Drive-Cycles

FinancialCalculations

NumericalOptimizer

IC Engine-On ThresholdIC Engine-Off ThresholdBattery Storage Capacity

Battery Max Discharge Power

Net Present Value (NPV)of investment &

future savings ($)

4000

4000

4000 40004000

4500

4500

4500

4500 4500

5000

5000

5000

5000 5000

5500

5500

5500

5500

5800

5800

5800

5800

6020

6020

6020

60

80

Battery Storage Capacity (kWh)

Batt

ery

Dis

charg

e P

ow

er

(kW

)

NPV variation

2 4 6 8 10 12 14 16 18 20

10

20

30

40

50

60

70

40kW, 18kWhBattery cost: DOE goals

0

0

0

0

500

500

50

0

50

0

500

1000

1000

10

00

1000

1000

2000

2000

20

00

20002400

2400

2400

2600

26

00

28

00

Battery Storage Capacity (kWh)

Batt

ery

Dis

charg

e P

ow

er

(kW

)

NPV variation

2 4 6 8 10 12 14 16 18 2010

20

30

40

50

60

70

80

8kW, 2kWhBattery cost: present

Technical AccomplishmentsBattery Size Selection to Maximize Net Present Value

Process Results

Study performed in partnership with MathWorks

Collaborations

16

U.S.EPA, City of Chicago, University of Davis (through INL) provided real world drive cycles

Implementation of optimization algorithm with the MathWorks

Cross correlation

Distance vs. Max speed

Regression

-1.2-1-0.8-0.6-0.4-0.2Average deceleration

0.20.40.60.8 1Average acceleration

20 40 60Averagespeed

-4 -2Max

deceleration

1 2 3Max

acceleration

0 200040006000Time

50 100Max Speed

0 20 40 60Distance

-100 -50 0Pess

chargingper each cycle

100 200Pess

dischargingper each cycle

50 100150200-1.2

-1-0.8-0.6-0.4-0.2

Pess sized

Aver

age

dece

lera

tion 0.2

0.40.60.8

1

Aver

age

acce

lera

tion

2040

60

Aver

age

spee

d

-4

-2

Max

de

cele

ratio

n 123

Max

ac

cele

ratio

n 0200040006000

Tim

e50

100

Max

Sp

eed

0204060

Dist

ance

-100

-50

0

P ess

char

ging

per e

ach

cyc

le

100

200

P ess

di

scha

rgin

gpe

r eac

h

cyc

le

50100150200

P ess s

ized

0

4

8

12

16

20

Num

ber o

f occ

uren

ces

(%)

20 25 30 35 40 45 50 550

10

20

30

40

50

60

70

80

90

100

Cum

ulat

ive

Mea

n sp

eed

(%)

Mean speed (mile/h)

Mean=33.4 mile/hMedian=33.5 mile/hStd=6.8 mile/hNumber of Daily Drive =111

Distribution of Mean speed for Daily Drives

HWFET

LA92

UD

DS

US06

Cross correlation used to understand relations between key parameters (speed, acceleration, deceleration…)

Cycle characteristics compared to standard ones

Future Activities

Study impact of set of Real World Drive Cycle used on fuel displacement -> How much of the results can be generalized?

Develop and test vehicle level control strategies with trip recognition.

Understand comparison with standard drive cycles for conventional, HEVs and PHEVs (J1711)

Perform MonteCarlo analysis on the assumptions and control options to provide an uncertainty value.

Use the existing process (i.e., run simulations, automated post-processing…) to assess fuel displacement potential for Medium and Heavy duty applications.

17

18

Summary

Real World Drive Cycles (RWDC) were used to assess to fuel consumption potential of different vehicles (powertrain, component sizing, vehicle control)

Different vehicle control philosophies and tuning parameters were selected based on fuel efficiency, drive quality and battery RMS current.

The impact of driving distance and driver aggressiveness was also evaluated.

Future studies will focus on determining how much these results can be generalized using different set of RWDC as well as compare the results with standard test procedure.

18

Additional Slides

19

20

List of Publications Vijayagopal, R., Kwon, J., Rousseau, A., P. Maloney (MathWorks), “Maximizing

Net Present Value of a Series PHEV by Optimizing Battery Size and Control”, SAE 2010-01-0037, SAE Convergence, Detroit, November 2010

Karbowski, K, Freiherr von Pechmann, S. Pagerit, J. Kwon, A. Rousseau, “Fair Comparison of Powertrain Configurations for Plug-In Hybrid Operation using Global Optimization”, SAE paper 2009-01-1383, SAE World Congress, Detroit, April 2009

M. Fellah, G. Singh, A. Rousseau, S. Pagerit, “Impact of Real-World Drive Cycles on PHEV Battery Requirements”, SAE paper 2006-01-0377, SAE World Congress, Detroit, April 2009

A.Moawad, G. Singh, S. Hagspiel, M. Fellah, A. Rousseau, “Real World Drive Cycles on PHEV Fuel Efficiency and Cost for Different Powertrain and Battery Characteristics”, EVS24, Norway, May 2009 , WEVA Journal, ISSN 2032-6653

G. Faron, S. Pagerit, A. Rousseau, “Evaluation of PHEVs Fuel Efficiency and Cost Using MonteCarlo Analysis “,EVS24, Norway, May 2009 , WEVA Journal, ISSN 2032-6653

20

21

Approach - Control Strategies Considered

Study

Power Split

Series

4kWh

8kWh

12kWh

16kWh

Load Following Engine Power

Thermostat


Thermostat


Optimal Engine Power

Differential Engine Power


Optimal Engine Power

Differential Engine Power

All these options were simulated on the RWDCs(source EPA 2005 Kansas City Cycles – 110 trips)

Each tuned for 10, 20, 30, 40 & 50 miles Charge Depleting (CD) range on the

UDDS

Differential Engine Power Strategy

22

The engine is started when wheel power demand exceeds a certain threshold.

It then provides the difference between the wheel power demand and the power threshold.

Load Following Strategy

23


It then provides the full wheel power, i.e. it is load following

Constant Optimal Engine Strategy

24


Engine then operates at its optimal power.

If engine power exceeds wheel power demand, the battery is charged.

Battery charging

Thresholds Definition for Slides 12, 13, 14

25

Distance (miles)– short 0 to 32,

– medium 32 to 61,

– long 61 to 90

Speed (mph): – low 0-31,


– high 42 to 55

Aggressiveness (W/mile): – low 0 to 407,


– high 714 to 1066

Documents

Impact of Driving Behavior on PHEV Fuel Consumption for … · 2010-07-09 · 2009 DOE Hydrogen Program and Vehicle Technologies . Annual Merit Review . June 08, 2010. Aymeric Rousseau