SIMULATED REAL-WORLD ENERGY 

IMPACTS OF A THERMALLY SENSITIVE 

POWERTRAIN CONSIDERING VISCOUS 

LOSSES AND ENRICHMENT

Eric Wood, Jeffrey Gonder, Sean Lopp

National Renewable Energy Laboratory

Forrest Jehlik

Argonne National Laboratory

SAE Thermal Management Systems Symposium 

Sept 23, 2014 – Denver, Colorado

NREL/PR-5400-62443

NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.
SAE INTERNATIONAL

• Several factors influence fuel economy, including:

o Drive cycle (speed, acceleration, idle time)

o Road grade

o Vehicle thermal state (hot start vs. cold start)

o Ambient conditions

o Cabin HVAC loads

• This effort seeks to improve understanding of real-world fuel economy 

by combining large datasets of operating conditions with high fidelity 

vehicle models supported by comprehensive test data to:

o Improve public understanding of fuel economy variation

o Inform industry testing procedures

o Identify avenues for OEMs to improve real-world MPG (and earn credit!)

Your MPG Will Vary...

2

HVAC = heating, ventilation, and air conditioning

OEM = original equipment manufacturer

MPG = miles per gallon
SAE INTERNATIONAL

• Present dynamometer data from 2011 Ford Fusion tested at Argonne 

National Laboratory’s (ANL’s) Advanced Powertrain Research Facility 

(APRF)

• Propose system of equations to describe internal combustion engine 

(ICE) efficiency relative to thermal state and document goodness of fit

• Describe interface between ICE models and NREL’s High Performance 

Computing Environment for drive cycle simulation

• Discuss simulated fuel economy sensitivity to drive cycle, thermal state, 

and ambient conditions

• Identify potential for insulated engine oil and coolant to reduce warm-up 

times, prolong cool-down times, and improve real-world fuel economy

Outline

3
SAE INTERNATIONAL

• Present dynamometer data from 2011 Ford Fusion tested at Argonne 

National Laboratory’s (ANL’s) Advanced Powertrain Research Facility 

(APRF)

• Propose system of equations to describe internal combustion engine 

(ICE) efficiency relative to thermal state and document goodness of fit

• Describe interface between ICE models and NREL’s High Performance 

Computing Environment for drive cycle simulation

• Discuss simulated fuel economy sensitivity to drive cycle, thermal state, 

and ambient conditions

• Identify potential for insulated engine oil and coolant to reduce warm-up 

times, prolong cool-down times, and improve real-world fuel economy

Outline

4
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ANL APRF & Vehicle Instrumentation

5

• 2011 Ford Fusion Thermal Evaluation Vehicle 

o Four-cylinder, six-speed transmission representative of a modern mid-size vehicle 

o More than 27 thermal channels of data (engine oil, transmission oil, engine coolant, 

cabin temperatures)

Catalyst Temperatures Exhaust Runner Temp 

Coolant Temperatures 

Post-cat. Exhaust Temp 

Coolant Flows Cabin Temperatures

Photos Credit: Forrest Jehlik
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Fusion Test Matrix

6

Variable Values

Drive Cycle UDDSx2, US06x2

Start Condition Hot Start, Cold Start

Test Cell Temperature 0°F, 20°F, 72°F, 95°F

16 tests 

in total

Test matrix designed to cover 

representative range of drivecycle conditions, ICE thermal 

states, and ambient 

temperatures

Expect wide range of test 

conditions to provide best and 

worst case ICE viscosity and 

enrichment responses

*Enrichment used here to denote incremental fuel 

rate increase to accelerate catalyst heating in the 

exhaust line on startup

Credit: Forrest Jehlik
SAE INTERNATIONAL

• Thermal response of engine coolant and engine oil is presented 

for cold-start Urban Dynamometer Driving Schedule (UDDS) 

cycles over a sweep of ambient conditions

• Oil response lags coolant with both fluids reaching steady-state 

temperatures that are dependent on ambient conditions

Fusion Test Data

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• Powertrain thermal state significantly impacts fuel consumption 

with both hot- and cold-start cycles experiencing penalties 

relative to hot ambient conditions

• The real-world impact of cold starts and cold operating 

conditions is highly drive-cycle and climate dependent

Fusion Test Data

8

6.6% 21.7%
SAE INTERNATIONAL

• Present dynamometer data from 2011 Ford Fusion tested at Argonne 

National Laboratory’s (ANL’s) Advanced Powertrain Research Facility 

(APRF)

• Propose system of equations to describe internal combustion engine 

(ICE) efficiency relative to thermal state and document goodness of fit

• Describe interface between ICE models and NREL’s High Performance 

Computing Environment for drive cycle simulation

• Discuss simulated fuel economy sensitivity to drive cycle, thermal state, 

and ambient conditions

• Identify potential for insulated engine oil and coolant to reduce warm-up 

times, prolong cool-down times, and improve real-world fuel economy

Outline

9
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ICE Thermal Model: System of Equations

10

Sub-Model Governing Equation Supporting 

Equations

Engine Efficiency

Catalyst 

Temperature

Oil Temperature

Coolant 

Temperature

ffffffff = ff1 PPoooooo, TToooooo + ff2(TTcccc )

ff2(TTcccc ) = max(0, aa1 ∗ ( 2∗ TTcccccc− 3 −1))

ff1 PPoooooo, TToooooo = aa0 +

aa1,1PPoooooo

3 + aa1,2PPoooooo2 + aa1,3PPoooooo +

aa2,1dd oooooo

3 + aa2,2dd oooooo2 + aa2,3dd oooooo +

aa3,1PPoooooo

3dd oooooo

3 + aa3,2PPoooooo

2dd oooooo

2 + aa3,3PPoooooodd oooooo

dd oooooo = TT0 − TToooooo

TṪ

cccc = h TT aaaa − TTcccc + αα(PPoooooo − PP ii)

mmcccc

h = aah1vvvvvv + aah2

αα = aaαα1TTcccc + aaαα2

TṪ

oooooo = h1 TT aaaa − TToooooo + h2 TTcc − TToooooo + αα(PPoooooo − PP ii)

mmoooooo

h1 = aa1vvvvvv + aa2

TṪ

cc = h1 TT aaaa − TTcc + h2 TToooooo − TTcc + αα(PPoooooo − PP ii)

mmcc

ii TTcc < TTss :

h1 = aa1vvvvvv + aa2

ee :

h1 = aa3vvvvvv + aa4

System of equations 

developed to capture 

primary system dynamics
SAE INTERNATIONAL

ICE Thermal Model: System of Equations

11

Sub-Model Governing Equation Supporting 

Equations

Engine Efficiency

Catalyst 

Temperature

Oil Temperature

Coolant 

Temperature

ffffffff = ff1 PPoooooo, TToooooo + ff2(TTcccc )

ff2(TTcccc ) = max(0, aa1 ∗ ( 2∗ TTcccccc− 3 −1))

ff1 PPoooooo, TToooooo = aa0 +

aa1,1PPoooooo

3 + aa1,2PPoooooo2 + aa1,3PPoooooo +

aa2,1dd oooooo

3 + aa2,2dd oooooo2 + aa2,3dd oooooo +

aa3,1PPoooooo

3dd oooooo

3 + aa3,2PPoooooo

2dd oooooo

2 + aa3,3PPoooooodd oooooo

dd oooooo = TT0 − TToooooo

TṪ

cccc = h TT aaaa − TTcccc + αα(PPoooooo − PP ii)

mmcccc

h = aah1vvvvvv + aah2

αα = aaαα1TTcccc + aaαα2

TṪ

oooooo = h1 TT aaaa − TToooooo + h2 TTcc − TToooooo + αα(PPoooooo − PP ii)

mmoooooo

h1 = aa1vvvvvv + aa2

TṪ

cc = h1 TT aaaa − TTcc + h2 TToooooo − TTcc + αα(PPoooooo − PP ii)

mmcc

ii TTcc < TTss :

h1 = aa1vvvvvv + aa2

ee :

h1 = aa3vvvvvv + aa4

Coefficients fit using 

unconstrained non-linear 

optimization method 

(Nelder-Mead) in MATLAB
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Engine Efficiency Model

12

ffffffff = ff1 PPoooooo, TToooooo + ff2(TTcccc )

ff2(TTcccc ) = max(0, aa1 ∗ ( 2∗ TTcccccc− 3 −1))

ff1 PPoooooo, TToooooo = aa0 +

aa1,1PPoooooo

3 + aa1,2PPoooooo2 + aa1,3PPoooooo +

aa2,1dd oooooo

3 + aa2,2dd oooooo2 + aa2,3dd oooooo +

aa3,1PPoooooo

3dd oooooo

3 + aa3,2PPoooooo

2dd oooooo

2 + aa3,3PPoooooodd oooooo

dd oooooo = TT0 − TToooooo

Cumulative Fuel Error

UDDS US06

Ambient Temp Cold Start Hot Start Cold Start Hot Start

0F -3.9% 1.5% -5.0% 2.5%

20F 0.5% 1.9% 2.5% 5.2%

72F -1.7% -1.3% -0.5% -0.9%

95F -4.1% -2.0% -0.5% -2.8%

Goodness of fit statistics

(predictive accuracy of model to be evaluated relative to

5 cycle test data by end of FY14)

Measured vs 

modeled fueling rate

Model Structure
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Catalyst Thermal Model

13

Warm-up phase

(engine on)

Cool-down phase

(engine off)

Instantaneous RMS Error (deg C)

UDDS US06

Ambient Temp Cold Start Hot Start Cold Start Hot Start

0F 69.5 26.9 70.3 24.4

20F 54.5 24.8 53.5 23.6

72F 37.5 19.8 50.1 24.6

95F 34.6 20.0 38.4 24.6

TṪ

cccc = h TT aaaa − TTcccc + αα(PPoooooo − PP ii)

mmcccc

h = aah1vvvvvv + aah2 αα = aaαα1TTcccc + aaαα2

Goodness of fit statistics

(predictive accuracy of model to be evaluated relative to

5 cycle test data by end of FY14)

Model Structure
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Oil Thermal Model

14

Warm-up phase

(engine on) Cool-down phase

(engine off)

TṪ

oooooo = h1 TT aaaa − TToooooo + h2 TTcc − TToooooo + αα(PPoooooo − PP ii)

mmoooooo

h1 = aa1vvvvvv + aa2

Instantaneous RMS Error (deg C)

UDDS US06

Ambient Temp Cold Start Hot Start Cold Start Hot Start

0F 5.2 7.2 5.4 2.0

20F 4.9 4.1 5.5 1.9

72F 5.7 6.1 8.5 2.5

95F 6.3 8.1 6.7 4.6

Goodness of fit statistics

(predictive accuracy of model to be evaluated relative to

5 cycle test data by end of FY14)

Model Structure
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Coolant Thermal Model

15

Warm-up phase

(engine on) Cool-down phase

(engine off)

Instantaneous RMS Error (deg C)

UDDS US06

Ambient Temp Cold Start Hot Start Cold Start Hot Start

0F 7.0 9.2 7.4 3.9

20F 5.1 5.4 6.9 3.3

72F 6.8 4.3 12.5 5.9

95F 6.5 6.0 10.9 9.1

TṪ

cc = h1 TT aaaa − TTcc + h2 TToooooo − TTcc + αα(PPoooooo − PP ii)

mmcc

ii TTcc < TTss :

h1 = aa1vvvvvv + aa2

ee :

h1 = aa3vvvvvv + aa4

Goodness of fit statistics

(predictive accuracy of model to be evaluated relative to

5 cycle test data by end of FY14)

Model Structure
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Model Error for All 16 Test Cycles

16

Assume perpetually 

“hot” component maps

Model oil/coolant/cat 

nodes as lumped 

parameters
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Model Error for All 16 Test Cycles

17

Isothermal model does not capture sensitivity to thermal state 

at key-on or impact of ambient temperature
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Model Error for All 16 Test Cycles

18

Model error is significantly reduced (especially under cold start 

conditions) by incorporating simple lumped capacitance thermal models
SAE INTERNATIONAL

• Present dynamometer data from 2011 Ford Fusion tested at Argonne 

National Laboratory’s (ANL’s) Advanced Powertrain Research Facility 

(APRF)

• Propose system of equations to describe internal combustion engine 

(ICE) efficiency relative to thermal state and document goodness of fit

• Describe interface between ICE models and NREL’s High Performance 

Computing Environment for drive cycle simulation

• Discuss simulated fuel economy sensitivity to drive cycle, thermal state, 

and ambient conditions

• Identify potential for insulated engine oil and coolant to reduce warm-up 

times, prolong cool-down times, and improve real-world fuel economy

Outline

19
SAE INTERNATIONAL

Modeling Environment

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.

Exercise calibrated models over a large sweep of usage conditions to 

evaluate the interplay between travel time, driving behavior, ambient 

temperature, road grade, and ICE thermal response

Data Element Source Notes

Drive Cycles/ 

Trip Distributions

NREL Transportation 

Secure Data Center

The TSDC houses hundreds of thousands of real-world 

drive cycles from vehicles across the country.

Climate Data NREL National Solar 

Radiation Database 

Home to TMYs from hundreds of U.S. locations, each

containing hourly climate data.

Elevation/ 

Road Grade

USGS National 

Elevation Dataset

Raw USGS elevations are filtered to remove anomalous 

data and produce smooth road grade curves.

FASTSim = Future Automotive Systems 

Technology Simulator

TMY = Typical Meteorological Year

TSDC = Transportation Secure Data Center

USGS = United States Geological Survey

ICE Thermal Model
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Apply Model to Drive Cycle and Climate Data

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One week of simulation One week of drive-cycle simulation

Overlay travel history with 

meteorological data

Model interplay of drive/park sequence 

with vehicle thermal state
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Apply Model to Drive Cycle and Climate Data

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Coolant temp leads oil temp in 

warm-up and cool-down phases

One week of simulation Three hours of drive-cycle simulation
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Apply Model to Drive Cycle and Climate Data

23

One week of simulation Twenty minutes of drive-cycle simulation

Coolant and oil temps are linked; 

both are functions of vehicle speed
SAE INTERNATIONAL

• Present dynamometer data from 2011 Ford Fusion tested at Argonne 

National Laboratory’s (ANL’s) Advanced Powertrain Research Facility 

(APRF)

• Propose system of equations to describe internal combustion engine 

(ICE) efficiency relative to thermal state and document goodness of fit

• Describe interface between ICE models and NREL’s High Performance 

Computing Environment for drive cycle simulation

• Discuss simulated fuel economy sensitivity to drive cycle, thermal state, 

and ambient conditions

• Identify potential for insulated engine oil and coolant to reduce warm-up 

times, prolong cool-down times, and improve real-world fuel economy

Outline

24
SAE INTERNATIONAL

Simulation Results

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Simulated fuel economy by climate 

data and week of year

Simulated fuel economy by drivecycle data and week of year

Box and whiskers segment results by quartile

Markers denote statistical outliers

39M miles of simulated 

driving in each plot
SAE INTERNATIONAL

• Aggregate fuel consumption rates reported for hundreds of week-long vehicle 

histories simulated over matrix of representative drive cycle sets and climates

• Engine thermal effects accounted for 4.8% of total simulated fuel consumption

• Enrichment effects accounted for 2.7% of total simulated fuel consumption

• Results slightly under-predict fuel consumption relative to simulated and adjusted 

EPA 5-cycle test procedure (additional contributions to be added as future work)

Simulation Results

26
SAE INTERNATIONAL

• Present dynamometer data from 2011 Ford Fusion tested at Argonne 

National Laboratory’s (ANL’s) Advanced Powertrain Research Facility 

(APRF)

• Propose system of equations to describe internal combustion engine 

(ICE) efficiency relative to thermal state and document goodness of fit

• Describe interface between ICE models and NREL’s High Performance 

Computing Environment for drive cycle simulation

• Discuss simulated fuel economy sensitivity to drive cycle, thermal state, 

and ambient conditions

• Identify potential for insulated engine oil and coolant to reduce warm-up 

times, prolong cool-down times, and improve real-world fuel economy

Outline

27
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Insulate Engine Oil + Coolant

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One week of simulation Thirty hours of drive-cycle simulation

Adjust thermal model to 

approximately double time 

constant on engine oil cooling
SAE INTERNATIONAL

• Insulated model compared to baseline under simulated EPA 5-cycle test 

procedure and large sweep of real-world drive cycles and climates

• Simulated 5-cycle test procedure netted 0.7% fuel economy 

improvement

o Byproduct of reduced warmup time during cold start tests (Federal Test 

Procedure (FTP) and cold FTP)

• Simulated real-world cycles resulted in 2.0% average fuel economy 

improvement

o 5th percentile vehicle history: 1.3% improvement

o 95th percentile vehicle history: 6.6% improvement

o In addition to reduced warm-up times, real-world drive cycles benefit from 

higher temperatures at start of drive cycles (due to prolonged cool-down 

times)

Insulate Engine Oil + Coolant

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SAE INTERNATIONAL 30

• Preliminary results suggest that the real-world benefit of certain fuel 

efficiency technologies may differ from that reflected by 5-cycle test 

procedure

o Merging of large drive cycle and climate datasets with vehicle models 

trained on laboratory test data provides an improved understanding of 

real-world fuel economy

• Future work will consider additional...

o Real-world effects (drivetrain efficiency at cold temperatures, sensitivity of 

road load to climate, and cabin HVAC energy requirements)

o Vehicle models (hybrid electric vehicle, sport utility vehicle, full-size truck)

o Fuel economy improvement strategies (further component insulation, 

exhaust heat recovery)

Conclusions & Future Work
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• This work is funded by the DOE Vehicle 

Technologies Office

• We appreciate the support provided by our 

DOE program managers

• Lee Slezak

• David Anderson

• Technical questions regarding this work 

should be directed to Eric Wood at 

303.275.3290 or eric.wood@nrel.gov

Acknowledgments

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Thanks! Questions?

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