NREL/TP-473-7260 • UC Category: 1501 • DE94011859

Current Hybrid Electric Vehicle 

Performance Based on Temporal 

Data from the World’s Largest 

HEV Fleet 

Keith Wipke 

Prepared for the 12th International 

Electric Vehicle Symposium, Anaheim, 

California, December 5-7, 1994

National Renewable Energy Laboratory 

1617 Cole Boulevard 

Golden, Colorado 80401-3393 

A national laboratory of the U.S. Department of Energy 

Managed by Midwest Research Institute 

for the U.S. Department of Energy 

under contract No. DE-AC36-83CH10093 

September 1994 
NREL/TP-473-7260

Current Hybrid Electric Vehicle 

Performance Based on Temporal 

Data from the World’s Largest 

HEV Fleet 

Keith Wipke 

Prepared for the 12th International 

Electric Vehicle Symposium, Anaheim, 

California, December 5-7, 1994

National Renewable Energy Laboratory 

1617 Cole Boulevard 

Golden, Colorado 80401-3393 

A national laboratory of the U.S. Department of Energy 

Managed by Midwest Research Institute 

for the U.S. Department of Energy 

under contract No. DE-AC36-83CH10093 

Prepared under Task No. HV412030 

September 1994
NOTICE 

This report was prepared as an account of work sponsored by an agency of the United States 

government. Neither the United States government nor any agency thereof, nor any of their employees, 

makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, 

completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents 

that its use would not infringe privately owned rights. Reference herein to any specific commercial 

product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily 

constitute or imply its endorsement, recommendation, or favoring by the United States government or any 

agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect 

those of the United States government or any agency thereof. 

 
CURRENT HYBRID ELECTRIC VEHICLE PERFORMANCE BASED ON TEMPORAL 

DATA FROM THE WORLD'S LARGEST HEV FLEET 

K. Wipke 

National Renewable Energy Laboratory 

1617 Cole Blvd. 

Golden, CO 80401 

Abstract 

The United States Department of Energy (DOE) procured new data collection equipment for the 

42 vehicles registered to compete in the 1994 Hybrid Electric Vehicle (HEV) Challenge, 

increasing the amount of information gathered from the world's largest fleet of HEVs. Data were 

collected through an on-board data storage device and then analyzed to determine effects of 

different hybrid control strategies on energy efficiency and driving performance. In this paper, 

the results of parallel hybrids versus series hybrids with respect to energy usage and acceleration 

performance are examined, and the efficiency and performance of the power-assist types are 

compared to that of the range-extender types. Because on-board and off-board electrical 

charging performance is critical to an efficient vehicle energy usage cycle, charging performance 

is presented and changes and improvements fiom the 1993 HEV Challenge are discussed. Peak 

power used during acceleration is presented and then compared to the electric motor 

manufacturer ratings. Improvements in data acquisition methods for the 1995 HEV Challenge 

are recommended. 

Introduction 

The 1994 HEV Challenge was a collegiate competition held at the Lawrence Technological 

University in Southfield, Michigan, June 14-20. The week-long competition and the year of 

vehicle preparation involved 42 schools from the United States and Canada. The HEV 

Challenge began in 1993 with a total of 30 vehicles in two classes: 12 vehicles that were built 

fiom the ground up (Ground-Up Class) and 18 converted 1992 Ford Escort station wagons 

(Escort Conversion Class). The 1994 HEV Challenge included a new class--the Saturn 

Conversion Class--which added 12 new schools to the 28 returning schools. The HEV Challenge 

involved a series of competitive events, including: emissions testing, technical papers, design 

review presentations, acceleration, range, road rally, energy economy, and a timed performance 

test. Figure 1 shows the University of Texas, Austin during the timed performance test. Before 

any of the teams could compete in the dynamic events, they had to pass rigorous safety 
inspections and dynamic qualifying, including acceleration, braking, U-turn, slalom, and a 

figure-8. 

Figure 1 

The University of Texas, Austin HEV During Commuter Challenge Event 

The mission of the HEV Challenge is to provide future engineers with exceptional educational 

opportunities to design, build, and test "real-world'' hybrid electric vehicles. The students' goal is 

to develop innovative and environmentally responsible vehicles that combine electric and 

thermal power to improve mileage and reduce emissions while maintaining performance 

comparable to conventional vehicles. To document the performance improvements in the 

vehicles and facilitate scoring of the energy efficiency events, on-board data acquisition hardware 

was provided to each school and data were collected after each event in both the 1993 and 1994 

HEV Challenges. A detailed analysis of all electric energy usage data fiom the 1993 HEV 

Challenge and other advanced vehicle competitions was completed; the analysis verified the 

expected effects of mass, speed, and distance on energy usage.' Because of the more advanced 

data acquisition system (DAS) used in the 1994 HEV Challenge, additional data were collected 

that allowed a more detailed understanding of each individual vehicle. 

Data Acquisition Systems Employed 

Back-up System from 1993 

The data acquisition system used in 1993 was an energy meter fiom Cruising Equipment that 

measured voltage, current, and time, and then integrated the power over time to calculate the net 

energy (kwh) used fiom the main battery pack.*.' A serial port could print out the voltage and 

current every second, but it required a laptop to record data for the duration of the event. 

Because 30 laptop computers were not available, no temporal data were collected during the 

1993 competition. This system was already installed in three-fourths of the vehicles and was 

kept in the vehicles for the 1994 Challenge as a back-up energy meter. 
1994 Data Acquisition System 

The primary DAS used in the 1994 HEV Challenge was called the Autologger, designed by 

Instrumental ~olutions.~ A competitive procurement process was used to evaluate and select the 

DAS for the 1994 HEV Challenge. The Autologger had the following features: 

Four analog channels measured: two currents and two voltages. 

Optical isolation from high voltage on all four analog channels. 

Measurement of distance and velocity. 

Monitoring of auxiliary power unit (APU) odoff activity. 

128K of on-board memory to store 1 -second averages of all channels sampled, resulting in 

6 hours of continuous second-by-second data storage. 

High sampling rate of 2500 Hz. 

Intelligence to collect data only when the vehicle was "keyed-on." 

Ability to download a summary of the energy data and a complete second-by-second log of 

all of the data stored in memory. 

Difficulties encountered with new DA S 

A number of problems were encountered with both the new DAS hardware and the way the 

students installed and wired the DASs in their vehicles that prevented complete data from being 

collected from all of the schools. First, not all of the schools had their hardware wired correctly, 

with one common problem being the APU odoff activity channel. Second, the DASs were often 

mounted in electrically and magnetically "noisy" locations under the hood, which might have 

been solved prior to the competition if the students had more time for their own testing. Finally, 

the on-board software occasionally got corrupted on ignition "key-on," causing some data to be 

lost by altering the program memory. 

All temporal data results presented here will be based only on the data that has been determined 

to be reasonable, which comprises data from 19 schools. One major advantage of the new DAS 

is that it allows this type of determination to be made by plotting the second-by-second voltages, 

currents, speeds, and APU activity, making clear which schools had noise problems or 

incomplete data. Prior to the 1994 HEV Challenge, all HEV and electric vehicle (EV) 

competition energy data were "black box" data making it difficult to determine its 

reasonableness. 

HEV Performance Analysis 

Types of Drivetrains and HEV Control Strategies 

Parallel and Series Drivetrains. There were three main types of hybrid vehicle drives used 

in the 1994 Challenge: parallel, series, and drives that could be switched between series and 

parallel. Parallel drive vehicles have a direct mechanical connection between the APU and the 

wheels, such as a transmission. Series vehicles have no such mechanical connection, with all 

motive power being transferred electrically to an electric motor that drives the wheels. The 
vehicles that had a switchable series/parallel configuration could take advantage of the 

load-leveling properties of a series configuration during low-speed stop-and-go city driving and 

use the highly efficient parallel drive configuration at higher speeds with a more constant loadn5 

Power-assis t and Range-extender. A large number of titles are assigned to hybrid vehicles 

based on their APU and battery pack size and power ratings, but discussion here will be limited 

to power-assist and range-extender vehicles. Range-extender vehicles are so named because they 

are essentially electric vehicles that have on-board charging capability to extend the electric-only, 

or zero-emission vehicle (ZEV) driving range. Power-assist vehicles are on the other side of the 

spectrum, with the internal combustion engine (ICE) providing most of the power and range and 

the electric portion of the vehicle serving to "assist" the ICE during hill climbs and accelerations. 

The electric energy storage (normally batteries) also serves as an energy buffer to capture extra 

energy from the ICE and from regenerative braking. Included in the competition rules for each 

class are requirements that steer each class toward a different type of hybrid. The Ground-Up 

and Escort Conversion vehicles from the 1993 Challenge were encouraged to be range-extender 

vehicles with a 64.4 km ZEV range and 241.5 km total range. The Saturn Conversion vehicles 

added in the 1994 Challenge were encouraged to be power-assist vehicles by reducing their 

required ZEV range to 8.05 km, increasing the required acceleration performance, and increasing 

the HEV range to 483 km. 

Acceleration Event 

The acceleration event was held in the morning of the same day that the range event was held, at 

the GM Milford Proving Ground on a 3.2 krn level straightaway. The event provided an 

opportunity to see the actual acceleration velocity profiles for the first time in the history of the 

engineering research competitions. Because voltage and current were also being measured, the 

peak powers used by the electric drives during the acceleration runs were also available. Timing 

lights were used at the start and finish of a 0.20 km section. Figure 2 shows a compilation of the 

acceleration profiles for all the vehicles for which calibrated velocity data were collected. Some 

of the schools did not get their vehicle running until just prior to the beginning of the events, 

preventing speed calibrations to be done on their vehicles. The thick black curves in Figure 2 

represent an envelope that encloses all of the acceleration profiles. The thinner solid curves 

represent parallel drive vehicles and the dashed curves represent the series drive vehicles. 

Vehicles that could switch between the two were assumed to be operating in parallel mode, 

which would most likely have the highest power. Unfortunately, only two series vehicles had 

calibrated acceleration profile data, but it is interesting to note that they are beaten out only by 

one vehicle, the parallel configured UC Santa Barbara. 

Comparing the official 0.20 km times from the acceleration event reveals a characteristic power 

difference between series and parallel vehicles. The range-extender vehicle acceleration times 

were compared for series and parallel vehicles in both HEV and ZEV modes, with the 

power-assist vehicles not included because they only ran in HEV mode. In HEV mode, the 

average acceleration times for the series vehicles was 17.0 seconds and 15.5 seconds for the 

parallel vehicles, while in ZEV mode the series vehicles had an average acceleration time of 15.3 

seconds compared to 17.3 seconds for the parallel vehicles. This shows that in ZEV mode, the 
series vehicles accelerate faster because their electric motors are sized appropriately for the 

maximum acceleration power, whereas the parallel vehicles have a smaller electric motor that 

was sized with the anticipation of combining it with mechanical power fiom the APU. This 

agrees with the general electric motor sizing reported by Burke, who reveals that parallel drives 

only need the electric 

A 

c E 

35 > 

- 0 

a 

> 

drive to provide 40% of the peak power.6 

a 

,- -* 

- series drive 

0 2 4 6 8 10 12 14 16 18 20 22 24 

Time (sec) 

Figure 2 

Acceleration Velocity Profile Comparison 

Another piece of information that can be extracted from the 1994 HEV Challenge data that could 

not be determined in any other competition was the peak electrical power draw from each vehicle 

during the acceleration runs (see Table 1). 

Table 1 

Peak Electric Power During Acceleration: Rating vs. Measured 

School 

Cal Poly Pomona 

Cal Poly SLO 

Jordan College 

Lawrence Tech 

NYIT 

U. of Maryland 

UC Davis 

Weber State 

Washington, S.L. 

Rated 

Peak Power 

(kw) 

33.6 

18 

n/a 

31.3 

n/a 

13 

45 

37.3 

59.7 

Measured 

Peak Power 

Run 1 (kW) 

39.9 

18.6 

30.5 

36.4 

27.2 

36.9 

38.5 

31.9 

15.8 

Measured 

Peak Power 

Run 2 (kW) 

27.9 

-- 

29.1 

28.8 

27.8 

43.5 

41.8 

29.5 

Percent Over 

Reported Peak 

Power Rating 

18.8 

3.3 

n/a 

16.3 

n/a 

234.6 

-7.1 

14.5 

-- -73.5 
The acceleration peak powers shown in Table 1 are representative of the overall peak power of 

their electrical drives, because the vehicles were pushed to their limits during this event. To gain 

some insight into how well the electric motors were rated on their peak power and to check the 

reasonableness of the measured values, the actual peak power can be compared to the rated peak 

power (as reported by the schools). Table 1 shows the peak power from the first two acceleration 

runs and that most schools' measured peak power was within plus or minus 10- 1 5% of their rated 

peak power. Washington University, St. Louis, and the University of Maryland had measured 

peak powers that were different by up to a factor of four from the manufacturer's rating. Further 

investigation would be required to determine why there was such a large difference. As an 

example of the temporal data collected during the acceleration event, Figure 3 shows the 

acceleration profile (and return trip) for Lawrence Technological University. Notice how as a 

load is applied to the batteries the voltage drops, and as the vehicle slows down and energy is 

recaptured fiom regenerative braking, the current switches polarity and the voltage increases. 

-- 

Regen. braking 

250 300 350 

Time (sec) 

Figure 3 

Temporal Acceleration Data fiom Lawrence Technological University 

Range Event 

The range event, which was a 3 hour and 20 minute timed event around the 3.42 km track at 

GM's Milford Proving Ground was useful for collecting energy usage data and looking at the 

hybrid control strategies employed by the schools. One of the benefits of the new DAS is that it 

enables the instantaneous electrical power usage to be calculated for any part of a recorded trip, 

however, the steep grades in the course used for the 1994 Challenge range event did not allow a 

constant driving load condition to be established (see Figure 4). The organizers of the 1995 HEV 

Challenge will try to hold the range event on a level track, with at least a few laps at several 

predetermined speeds to allow the power requirements and energy usage of each vehicle to be 
compared. A power analysis with parallel hybrids is difficult because the APU power is difficult 

to measure, suggesting that the constant road load test be run in ZEV mode for those vehicles. 

The differences in the driving conditions between 1993 and 1994 (track, speeds, temperature) are 

great enough that no comparisons between the two years will be attempted. Specific analysis of 

the cycling on and off of the APUs was not possible for two reasons: 1) many vehicles did not 

have this wiring hooked up correctly or at all, and 2) the hill was large enough that most vehicles 

ran the range event with their APU on the entire time. For fiu-ther examination of the effect of 

heat engine odoff operation, refer to simulation results obtained at the Idaho National 

Engineering Laboratory (INEL).' 

\\I are at the end d the hill 

n -- Voltage 

.... Current 

t - Filtered Veloa 1 Indicates APU is on 

Current usage is zero 

-100 I I I -60 

6000 6500 7000 7500 8000 

Time (sec) 

Figure 4 

Temporal Data fiom University of Maryland During Range Event 

Energy usage data was collected during the range event to allow comparisons to be made 

between the vehicles. Because complete electrical energy usage data were not collected from all 

vehicles with the Instrumental Solutions hardware, the relatively complete data set from the 

back-up system was used so that comparisons could be made between the different types and 

drivetrains of the vehicles. The way that the energy economy was determined was by taking the 

distance traveled in the range event divided by the total energy used, being made up of both fuel 

energy and electrical energy. To focus on the vehicle performance, the vehicles have been 

analyzed without including the effect of their charging efficiency, which will be done 

independently of vehicle performance in the next section. 

Comparing the average energy economy of the power-assist HEVs with the range-extender HEVs 

shows the range-extender vehicles being 45.8% more efficient (2.45 km/kWh vs. 1.68 krn/kWh) 

than the power-assist HEVs. There are a number of factors that contributed to this result: 1) The 

range-extender vehicles on average used a larger portion of their energy as electric energy from 

their batteries (20% electric for the range-extenders compared to 4% for the power-assist 
vehicles), avoiding the thermal energy conversion losses in converting fuel to useful power. 

2) The range-extender vehicles were competing for the second time, and had a year and a half 

longer than the power-assist schools to optimize their vehicles. 3) All power-assist vehicles were 

required to run on either methanol (M85) or ethanol (E95) blends of fuel, adding to the challenge 

of an efficient vehicle conversion. See Figure 5 for a comparison between the power-assist and 

range-extender HEVs. The bars show the energy economy in km/kWh, and the diamonds 

indicate the percentage of the total energy used that came from the batteries. Notice that the two 

vehicles whose energy usage was greater than 90% from their batteries had a high energy 

economy, as would be expected because the thermal energy conversion has already taken place 

independent of the vehicle's power system (in this case, at a powerplant). However, these two 

vehicles did not drive as far in the event as the other vehicles, and therefore would not be able to 

sustain their high energy economy for very long. A more complete energy comparison might 

include electrical powerplant losses and energy expended during he1 refining. Note that there 

has been no state-of-charge (SOC) correction performed on this energy usage data, as would be 

done during the standard emissions test procedure being developed by a Society of Automotive 

Engineers (SAE) committee. The effect of an SOC correction would be to increase the effective 

fuel required to return the batteries to the same SOC. This effect would be small except for the 

few vehicles with a large percentage of the energy coming from electricity. 

7 fEl Energy Economy 

- I I Group Average 

+ % Electric Energy 

HEV Type 

Figure 5 

Power-Assist and Range-Extender Comparison for Range Event 

Another distinguishing characteristic of HEVs is the drivetrain type--parallel or series. Based on 

the average energy economy of the vehicles competing in the range event in the 1994 HEV 

Challenge, the data collected show the series hybrids to be 27% more efficient than the parallel 

hybrids. The average energy economy was 1.96 km/kWh for the parallel vehicles and 2.49 

krn/kWh for the series vehicles. One of the main contributors to this could be the nature of the 

track used for the event and the minimum driving speeds required. Because there were no stops 

or starts during the event (except for driver changes every half hour) and because of the hill, the 

event may have favored series vehicles which could more easily do APU load-leveling by 
recapturing the energy fiom downhill braking and applying it to the hills. The advantages of the 

simpler, more robust series design require fewer student designed mechanical parts and less 

actual road testing of the vehicle (more of it can be done in the lab). Figure 6 shows a 

comparison between the parallel and series vehicles during the range event. 

Energy Economy 

+ % Electric Energy ' 

Group Average 

Type of drive 

Figure 6 

Parallel and Series Drivetrain Comparison for Range Event 

Electrical Charging Efficiency 

As was done in the 1993 HEV Challenge, Detroit Edison provided electrical charging stations for 

recharging the batteries of the hybrid vehicles in the 1994 HEV Challenge. The charging 

efficiency was calculated as the ratio of DC energy that flowed into the negative side of the main 

battery pack through a DC watt-meter, divided by the AC line energy that flowed through a 

standard house analog energy meter. Thus, the charging efficiency is always less than 100% with 

the system being more efficient the closer the value is to 100%. Table 2 shows the charging 

efficiency for the eight vehicles for which charging data were available in both 1993 and 1994. 

The values given represent the best out of five possible nights for charging. The data show that 

in seven out of the eight cases the schools were able to significantly increase their charging 

efficiency. The average charging efficiency for these four Escort Conversions increased 52.5%, 

and it increased 39.9% for the four Ground-Up vehicles. This is probably because three out of 

these four Ground-Up teams built completely new vehicles and had a lot of other issues to focus 

on, while the Escort Conversion teams were able to focus on fine tuning their existing vehicle. 

All of the vehicles for which charging efficiencies were measured were then averaged together as 

a fleet in both 1993 and 1994 and then compared in the bottom of Table 2. This data shows that 

better methods were used for collecting data in 1993 than 1994 because the number of schools 

providing good data almost doubled, excluding the Saturn vehicles, which did not have off-board 
charging. The increase in the amount of charging efficiency data was due in part to the fact that 

all vehicles were impounded every night for charging, even if the teams still had work they 

wanted to do on their vehicle. This removed the incentive to not charge and get more time to 

work on their vehicle. The fleet charging efficiencies in Table 2 show, more importantly, that the 

average fleet charging efficiency increased fiom 56% to 78% in one year, producing an increase 

of 39% fiom the 1993 values. The significance of this can not be understated because for 

range-extender vehicles the overall kmn equivalent fuel economy depends in large part on how 

much electrical energy is used. This has even more significance for pure electric vehicles for 

which the charging efficiency more directly impacts their overall equivalent fuel economy. 

Table 2 

Vehicle Charging Efficiency Comparison 

Escort Conversions 1 1993 1 1994 1 Increase 

Colorado School of Mines 1 0.45 1 0.82 1 80.4% 

Stanford University 

University of Illinois 

0.68 

Weber State University 

0.40 

Average 

0.80 

0.60 

- 

Cal. Poly, San Luis Obispo 

Cornell Universitv 

Suggestions for 1995 DAS 

With a new class of vehcles, the Neon Conversion Class, being added to the 1995 HEV 

18.4% 

0.68 

Ground-Up Class 

0.53 

Lawrence Technological University 

University of California, Davis 

Average 

Overall HEV Fleet Charging Efficiency 

Number of Vehicles With Charging Data 

Average Charging Efficiency 

Challenge and the potential for 30 returning schools, the competition data collection can be 

improved to ease the scoring of the event as well as getting good data for research purposes. A 

simple, reliable energy meter is required that can provide the data needed for scoring the energy 

economy event. A more sophisticated DAS is needed for a limited number of schools to look at 

the APU onloff cycling frequency, the power output fiom the generator on series vehicles, and 

other temporally dependent parameters. This detailed data provides the support for code 

validation efforts already underway with the 1994 HEV Challenge data. An added feature to the 

advanced DAS would be to manually control when data is being collected and stored because the 

ignition "key-on" provided only limited control of when data was collected. 

72.0% 

0.83 

0.83 

0.60 

39.4% 

0.78 

0.34 

0.46 

0.56 

12 

0.56 

52.5% 

0.68 

0.87 

-17.7% 

45.3% 

0.44 

0.94 

0.73 

23 

0.78 

28.9% 

103 .O% 

39.9% 

91.6% 

39.3% 
Conclusions 

Data was collected from the world's largest fleet of HEVs during the 1994 Hybrid Electric 

Vehicle Challenge using a new DAS with on-board data storage. The data were analyzed to 

determine the effects of different hybrid control strategies on energy efficiency and driving 

performance. During the range event, the range-extender vehicles were found to be 45.8% more 

efficient than the power assist vehicles, and the series vehicles were 27% more efficient than the 

parallel vehicles. The temporal data were used to calculate peak powers during the acceleration 

event, and it was found to be within 10-1 5% of the manufacturer's ratings for most vehicles. 

Charging efficiency data were collected and compared to the 1993 HEV Challenge charging data 

to reveal an increase of 39% in the average charging efficiencies fiom 1993 to 1994. The data 

collected during the 1995 HEV Challenge can be improved by simplifying the data collection 

performed on all vehicles and doing more sophisticated data collection on a limited number of 

vehicles. 

Acknowledgments 

The author wishes to thank the sponsors of the 1994 HEV Challenge for making the event 

possible: the U.S. Department of Energy, Natural Resources Canada, Saturn, and the SAE. The 

DAS hardware was made available on loan to the schools by DOE. The author would also like to 

thank Cassandra Quaintance, of NREL, for helping process 25 MB of raw data fiom the DAS, 

and Jeffrey Bomheim, of ANL, for compiling a summary of the vehicle data sheets the schools 

submitted. Finally, many thanks to all of the HEV teams for their cooperation and patience 

during data collection at the event. 

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Vehicle Student Competitions." Advancements in Electric and Hybrid Electric Vehicle 

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Cruising Equipment Co., "Installation Manual: Kilowatt-Hour+ Meter," Seattle, WA (1993). 

Instrumental Solutions, " Autologger Installation Manual," Ottawa, ON, Canada (1 994). 

A. Kalberlah, "Electric Hybrid Drive Systems for Passenger Cars and Taxis." Electric 

Vehicle Design and Development. SAE, SP-862 (1 99 1). 

A. F. Burke. "HybridIElectric Vehicle Design Options and Evaluations." Electric and Hybrid 

Vehicle Technology. SAE, SP-915, pp. 53-77 (1 992). 

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