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How hybrid-electric vehicles are different from conventional vehicles: The effect of weight and power on fuel consumption

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An increasingly diverse set of hybrid-electric vehicles (HEVs) is now available in North America. The recent generation of HEVs have higher fuel consumption, are heavier, and are significantly more powerful than the first generation of HEVs. We compare HEVs for sale in the United States in 2007 to equivalent conventional vehicles and determine how vehicle weight and system power affects fuel consumption within each vehicle set. We find that heavier and more powerful hybrid-electric vehicles are eroding the fuel consumption benefit of this technology. Nonetheless, the weight penalty for fuel consumption in HEVs is significantly lower than in equivalent conventional internal combustion engine vehicles (ICEVs). A 100 kg change in vehicle weight increases fuel consumption by 0.7 l/100 km in ICEVs compared with 0.4 l/100 km in HEVs. When the HEVs are compared with their ICEV counterparts in an equivalence model that differentiates between cars and sports-utility vehicles, the average fuel consumption benefit was 2.7 l/100 km. This analysis further reveals that a HEV which is 100 kg heavier than an identical ICEV would have a fuel consumption penalty of 0.15 l/100 km. Likewise, an increase in the HEV's power by 10 kW results in a fuel consumption penalty of 0.27 l/100 km.
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IOP PUBLISHING ENVIRONMENTAL RESEARCH LETTERS
Environ. Res. Lett. 2(2007) 014003 (8pp) doi:10.1088/1748-9326/2/1/014003
How hybrid-electric vehicles are different
from conventional vehicles: the effect of
weight and power on fuel consumption
CReynolds
1and M Kandlikar2,3,4
1Institute for Resources, Environment and Sustainability, University of British Columbia,
2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada
2Institute of Asian Research, University of British Columbia, 1855 West Mall, Vancouver,
BC, V6T 1Z2, Canada
3Liu Institute for Global Issues, University of British Columbia, 6476 NW Marine Drive,
Vancouver, BC, V6T 1Z2, Canada
E-mail: c.reynolds@ires.ubc.ca and mkandlikar@ires.ubc.ca
Received 26 January 2007
Accepted for publication 7 March 2007
Published 28 March 2007
Online at stacks.iop.org/ERL/2/014003
Abstract
An increasingly diverse set of hybrid-electric vehicles (HEVs) is now available in North
America. The recent generation of HEVs have higher fuel consumption, are heavier, and are
significantly more powerful than the first generation of HEVs. We compare HEVs for sale in
the United States in 2007 to equivalent conventional vehicles and determine how vehicle weight
and system power affects fuel consumption within each vehicle set. We find that heavier and
more powerful hybrid-electric vehicles are eroding the fuel consumption benefit of this
technology. Nonetheless, the weight penalty for fuel consumption in HEVs is significantly
lower than in equivalent conventional internal combustion engine vehicles (ICEVs). A 100 kg
change in vehicle weight increases fuel consumption by 0.7l/100 km in ICEVs compared with
0.4l/100 km in HEVs. When the HEVs are compared with their ICEV counterparts in an
equivalence model that differentiates between cars and sports-utility vehicles, the average fuel
consumption benefit was 2.7l/100 km. This analysis further reveals that a HEV which is
100 kg heavier than an identical ICEV would have a fuel consumption penalty of
0.15 l/100 km. Likewise, an increase in the HEV’s power by 10 kW results in a fuel
consumption penalty of 0.27 l/100 km.
Keywords: hybrid-electric vehicles, fuel consumption, performance, vehicle weight, system
power
1. Introduction
Hybrid-electric vehicles (HEVs) use batteries, electric motors,
regenerative braking and reduction of engine idling time to
enhance a conventional internal combustion engine. This
approach is a proven means of reducing the fuel consumption
and/or improving the performance of light-duty passenger
vehicles [1,2]. The fuel consumption of HEVs is lower for
4Author to whom any correspondence should be addressed.
a number of reasons: the electric motor provides a portion of
the power for propulsion, especially at high-load conditions
when the vehicle is accelerating; some of the vehicle’s inertial
energy can be recaptured through regenerative braking systems
and stored in vehicle batteries; an engine-stop feature reduces
idling fuel consumption whenever the car is coasting, braking,
or stopped5. It has been argued that policies are needed
5This feature is also employed by so-called ‘mild hybrids’, which are
essentially conventional vehicles with oversized starter motors. Mild hybrids
such as the Saturn VUE and the GM Silverado are excluded from this study.
1748-9326/07/014003+08$30.00 1 ©2007 IOP Publishing Ltd Printed in the UK
Environ. Res. Lett. 2(2007) 014003 C Reynolds and M Kandlikar
to reduce transportation fuel consumption, as part of a suite
of approaches to reduce carbon emissions worldwide [3–6].
Hybrid-electric technology is expected to play a significant
role in achieving this. Yet these studies estimate potential fuel
savings by simply scaling the fleet average fuel consumption
by a given percentage. In order to more accurately calculate
the magnitude of fuel savings, a more robust quantitative
analysis of the relationship between weight, performance and
fuel consumption of HEVs vis-`a-vis conventional internal
combustion engine vehicles (ICEVs) is needed.
Previous studies have successfully modeled the fuel
consumption, weight, and performance tradeoffs of HEVs
based on an assessment of one or two HEV models [7,8].
This study aims to add to that body of work by analyzing
specifications and fuel consumption data for 2007 model
year hybrid-electric vehicles and their ICEV counterparts in
the North American market. We begin by examining the
expanding hybrid fleet in North America, and present data on
the changing nature of the US HEV fleet as hybrid-electric
technology is adopted across a more diverse array of light-
duty passenger vehicle platforms. Using linear regression
models, we analyze how vehicle weight and power affect the
fuel consumption of HEVs and ICEVs independently, and then
we compare the set of currently available HEVs (2007 model
year) against a functionally equivalent set of conventional
ICEVs. The ‘equivalent set’ are ICEVs of the same make
and model, and with similar power. These analyses provide a
more accurate quantitative picture of the relationship between
fuel consumption, vehicle weight and system power, using
empirical data from commercially available vehicles.
2. Diversifying hybrid-electric vehicle fleet
Automotive manufacturers are offering an increasing variety
of HEV model types. In 2007, there were nine light-duty HEV
models available in the US, and this number is projected to
double in the next two to three years [9]. Figure 1shows
the annual and cumulative sales of HEVs in the US between
1999 and 2006, as well as the number of car and sports-
utility vehicle (SUV) models available in each year. SUVs
made up approximately 30% total hybrid sales in 2006. In
addition to the growing diversity of model offerings, HEV
annual sales continue to grow both in numbers and as a
proportion of the total light-duty vehicle sales. 2006 HEV
sales in the US represent approximately 1.6% of the year’s
new vehicle sales [10,11], with predictions of continued
increase [12]. Vehicle manufacturers publish performance
specifications for individual HEV models, including gasoline
engine size (displacement), vehicle curb weight, net hybrid-
electric system power6, and acceleration. These HEV
data are presented for all of the HEVs investigated in this
study (table 1). An investigation of air pollutant emissions
performance of HEVs is beyond the scope of this paper.
However, it should be noted that since HEVs were introduced
6Torque is another characteristic that can be used to compare performance,
since it influences vehicle acceleration. However, we have chosen system
power as it is more commonly presented as a measure of powertrain
performance, and it is directly related to torque through engine speed.
0
100
200
300
400
500
600
700
800
1999 2000 2001 2002 2003 2004 2005 2006
(1/0) ( 2/0) ( 2/0) (2 /0) (2 /0)
(6/3)
(4/2)
(3/1)
HEV Sales, 1000s
2004:
Toyota Prius 2nd
generation introduced;
Also, first hybrid-electric
SUV available for sale
(Ford Escape/Mercury
Mariner)
2006:
Nine HEV models
available;
SUV sales reach
29% of total 2006
sales
1999:
First HEVs sold
(17 Honda
Insights)
Cars: annual sales
SUVs: annual sales
Cumulative HEV sales
Figure 1. Car and sports-utility vehicle (SUV) shares of HEV annual
sales in the United States; annual SUV sales have been increasing
rapidly since their introduction in 2004. Cumulative HEV sales are
also shown, which are assumed to closely represent the number of
HEVs currently in use. Numbers in parentheses show numbers of
car/SUV models available for sale in a given year [11].
in North America, they have been lower-emitting than their
ICEV counterparts.
The combined fuel consumption rate is from US
Environmental Protection Agency (EPA) 2-cycle test results,
and refers to 45% highway and 55% city driving. The
EPA has recently proposed a new 5-cycle methodology that
will more accurately reflect actual driving behaviour and
corresponding fuel consumption [13]. The EPA predicts that
this methodology will increase combined fuel consumption
by 8% for conventional light-duty passenger vehicles, and by
16% for hybrid-electric vehicles. It is likely that the new
methodology will be implemented for the 2008 model year
in the US, so this study uses fuel consumption figures that
have been corrected by these factors (table 1). This approach
has been used before [14], and is supported by the reported
difference between real-world fuel consumption for the Toyota
Prius and its EPA 2-cycle fuel consumption rating [15].
From 2000 to 2006, the sales-weighted average hybrid-
electric vehicle in the US fleet has changed significantly, driven
largely by the introduction of new sports-utility and high-
performance HEV models. The average curb weight has
increased by 30%. Propelling this larger weight is a hybrid-
electric system that delivers 60% more power. The gasoline
engine component of this system is 43% larger in terms of
engine displacement. Some of the observed net power increase
is explained by the need to provide a larger vehicle with
acceptable performance. Over the same period, however, the
manufacturer-reported acceleration times also increased: the
average HEV in 2004 reaches 96.6kmh
1(60 miles per hour)
from a standing start in 20% less time than the average in 2003.
Because vehicle weight and power both strongly influence fuel
consumption, it is not surprising that average fuel consumption
has gone up by 15% with the shift towards higher-performance
HEVs (figure 2).
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Environ. Res. Lett. 2(2007) 014003 C Reynolds and M Kandlikar
Tab l e 1. Specifications of the HEV models considered in the analysis (ref: manufacturer specifications). The first-generation Toyota Prius
and the Honda Insight were discontinued in 2003 and 2006, respectively, and the reported fuel consumption for the Honda Accord was
improved for the 2007 model year.
Combined fuel
consumptionc
Hybrid-electric
vehicles Model
year Drive
typea
Trans-
missionb
Engine
displ.
(l)
Curb
weight
(kg)
Net
power
(kW)
Accel’n.
(0–96.6
km h1)
(s)
EPA
2-cycle
l/100 km
(mpg)
Corrected
l/100 km
(mpg)
Cars
Toyota Prius (1st Gen.) 2003 FWD ECVT 1.5 1237 75 12.7 4.9 (48) 5.7 (41)
Toyota Prius (2nd Gen.) 2006/7 FWD ECVT 1.5 1310 82 10.2 4.3 (55) 5.0 (47)
Toyota Camry 2006/7 FWD ECVT 2.4 1669 140 8.9 6.0 (39) 7.0 (34)
Honda Insight 2006 FWD CVT 1.0 896 53 10.7 4.2 (56) 4.9 (48)
Honda Civic 2006/7 FWD CVT 1.3 1304 82 11.0 4.7 (50) 5.5 (43)
Honda Accord 2006 FWD Auto 3.0 1627 189 6.5 8.4 (28) 9.7 (24)
Honda Accord 2007 FWD Auto 3.0 1635 189 6.5 7.6 (31) 8.8 (27)
Lexus GS 450h 2006/7 RWD ECVT 3.5 1875 254 5.2 9.0 (26) 10.5 (22)
Nissan Altima 2007 FWD ECVT 2.5 1588 148 6.0 (39) 7.0 (34)
Sports-utility vehicles
Toyota Highlander 2006/7 AWD Auto 3.3 1925 200 7.2 8.1 (29) 9.4 (25)
Ford Escape/Mercury Mariner 2006/7 AWD ECVT 2.3 1718 116 9.0 7.6 (31) 8.8 (27)
Lexus RX 400h 2006/7 AWD ECVT 3.3 1980 200 7.3 8.1 (29) 9.4 (25)
aFWD =front-wheel drive; RWD =rear-wheel drive; AWD =all-wheel drive.
bECVT =electronically controlled continuously variable transmission; CVT =continuously variable transmission;
Auto =automatic transmission.
cCombined fuel consumption represents 55% city, 45% highway driving.
2000 2002 2004 2006
80%
60%
40%
20%
0%
-20%
Relative Change, %
Curb Weight
Net hybrid system peak power
Combined fuel consumption
Figure 2. Vehicle performance trends over time for the average
HEV: curb weight, net hybrid system peak power, and fuel
consumption. Variability across models is indicated by the error bars
representing one (sales-weighted) standard deviation.
The changing nature of HEV technology can be gauged
by two further parameters, namely, the ratio of net system
power to vehicle curb weight and the ratio of power/engine dis-
placement. These parameters have been chosen because they
are primarily a function of the propulsion system, and they
offer insight into how hybrid-electric system technology has
evolved over time (figure 3). In comparison, fuel consump-
tion (another metric of performance) is influenced by vehicle
aerodynamics and curb weight, as well as the choice of test-
ing drive-cycle. Between 2000 and 2003, both parameters
stayed approximately constant, since only two vehicles, the
2004 20062000 2002
40
50
60
70
80
90
(Units indicated in legend)
Net Power / Vehicle Weight (W/kg)
Net Power / Engine Displacement (kW/litre)
Figure 3. Trends in net system power per vehicle weight (a measure
of vehicle performance) and net system power per engine volumetric
displacement (a measure of the technological development of the
propulsion system). Data dispersion is indicated by the weighted
standard deviation.
Toyota Prius and the Honda Insight, were offered for sale. In
2004, three new HEVs were released (the second-generation
Toyota Prius, the Honda Civic and the Ford Escape) and the
first-generation Prius was discontinued. The increased power
per unit vehicle weight between 2003 and the present indi-
cates a trend towards new vehicles having higher performance.
This is similar to what has been observed across the
whole light-duty vehicle fleet. For hybrid-electric propulsion
systems, power per engine displacement reveals technological
development; in other words, more system power is made
3
Environ. Res. Lett. 2(2007) 014003 C Reynolds and M Kandlikar
Tab l e 2. Vehicle weight, net system power, and corrected fuel consumption differences between 2007 model year HEVs and their ICEV
counterparts.
Hybrid-electric vehicles ‘Equivalent’ ICEV Vehicles
Delta weight
(kg)
Delta power
(kW)
Delta fuel
consumption
(l/100 km)
Carsa
Toyota Prius
2nd Gen. (I4) Toyota Matrix (I4) 61 12.03.25
Toyota Camry (I4) Toyota Camry (I4) 169 21.5 2.40
Honda Civic (I4) Honda Civic (I4) 84 22.42.21
Honda Accord (V6) Honda Accord (V6) 110 6.7 1.27
Lexus GS 450h (V6) Lexus GS 430 (V8) 175 37.3 1.60
Nissan Altima (I4) Nissan Altima (I4) 150 17.2 1.75
Sports-utility vehiclesa
Toyota Highlander (V6) Toyota Highlander (V6) 166 39.5 2.69
Ford Escape/Mercury Mariner (I4) Ford Escape/Mercury Mariner (I4) 165 1.5 2.75
Lexus RX 400h (V6) Lexus RX 350 (V6) 125 1.52.69
aInternal combustion engine type is indicated as follows: I4 =inline 4-cylinder engine; V6 and V8 refer to 6- and 8-cylinder
engines in ‘V’ configuration, respectively.
available for a given internal combustion engine size. This
parameter drops between 2000 and 2004 because the first-
generation Toyota Prius, which has a lower power per engine
displacement, captured an increasing proportion of sales.
Between 2003 and 2004 the power to engine displacement
ratio increased by about 10%, indicating that the newer HEV
technology was significantly improved.
3. Weight, power and fuel consumption
A number of factors can independently affect the fuel
consumption of conventional vehicles, including differences
in powertrain type and peak power, vehicle weight,
aerodynamics, rolling resistance, and accessory power
demand. In general, heavier and more powerful vehicles
have higher fuel consumption rates. Due primarily to
the significant difference in powertrain type, engineering
models have shown that conventional ICEVs have a different
relationship between vehicle inertial weight, net system power
and fuel consumption than HEVs [7,16]. Until recently there
have been insufficient HEV models to perform a statistical
comparison with conventional ICEVs that differ only in terms
of powertrain, so other analysts have used hypothetical hybrids
based on the best understanding of the technology [16]. To
evaluate the impact of current commercially available hybrid-
electric technology on light-duty vehicle fuel consumption,
we compare a set of nine model year 2007 HEVs to a set of
nine equivalent 2007 vehicles powered by internal combustion
engines. For the purposes of this study, ‘equivalence’ for any
given ICEV is defined as being the same make and model as
the HEV. Where different engine options are available for the
ICEV, the engine with the closest power is used7(table 2).
7The analyses shown in this paper were also performed with three other
assumptions for equivalent ICEs where different engine options were available.
These included equivalents based on similar engine size, smallest IC engines,
largest IC engines. Since there are not three powertrain options for each
equivalent ICEV, these different choices made little or no difference to the
conclusions of this study.
Only the Toyota Prius has no direct equivalent, so the Toyota
Matrix (a mid-size hatchback of similardimensions) is selected
as its counterpart. Automatic transmissions were chosen for
the equivalent ICEVs in the set, and each has the same drive
type (two-wheel or all-wheel drive) as their HEV counterpart.
Vehicle weight and engine power data were obtained from
the published manufacturer specifications, and combined fuel
consumption estimates were used, corrected using the EPA
factors as described earlier.
First, we examine how vehicle weight and net system
power affects the fuel consumption within each vehicle set
(HEVs and ICEVs). A simple regression model is used,
with fuel consumption (Fc in table 3) as the dependent
variable. Weight (100 kg) and power (10 kW) are examined
independently in turn as predictors of fuel consumption. Each
analysis yields significant results at the 95% confidence level
for both HEVs and ICEVs. The results of this regression
analysis are presented in table 3. A 100 kg increase in weight
(not considering power) results in 0.72 l/100 km increase in
fuel consumption for HEVs, and 0.77 l/100 km increase in
fuel consumption for ICEVs. Similarly, a 10 kW power
increase (not considering weight) results in 0.29 l/100 km
increase in fuel consumption for HEVs, and an almost identical
increase for ICEVs. When weight and power are evaluated
simultaneously as predictors of fuel consumption, weight is
found to be a significant predictor of fuel consumption for
ICEVs, but not power. However, we find that the HEV
sample does not produce significant results for weight and
power coefficients at the 95% confidence interval. This is not
surprising since weight and power are correlated (correlation
coefficient =0.84). Tolerance tests using inflated variation
factors [17] did not detect significant multi-collinearity, and the
Cook’s-D test [18] did not reveal any outliers.
One way of coping with high correlation between weight
and power is to directly estimate the relationship between
differences in fuel consumption and differences in weight and
power within each vehicle class (HEVs and ICEVs). This
significantly increases the sample size (N=36), and helps
4
Environ. Res. Lett. 2(2007) 014003 C Reynolds and M Kandlikar
Tab l e 3. Regression analyses results for HEVs and equivalent ICEVs. N=9 for the simple regressions, and N=36 for the pairwise
difference regression. Fuel consumption is the predicted variable.
Regression coefficients
Predicted variableaPredictor variablesbCW P 95% confidence intervals R2
HEVs
Fc C,W3.94 0.72c—(C:8.6, 0.7) (W: 0.44, 0.99) 0.84
Fc C,P3.34c0.29c(C: 1.2, 5.5) ( P: 0.16, 0.42) 0.8
Fc C,W,P1.5 0.43 0.14 (C:7,4) (W:0.03,0.9)
(P:0.6, 0.33)
0.89
Fc (pairwise
difference)
C,W,P0.16 0.4c0.14c(C:0.2, 0.51) (W: 0.23, 0.58)
(P: 0.07, 0.2)
0.85
Fcw C,P0.34 0.008c(C: 0.25, 0.44) (P: 0.002, 0.014) 0.6
ICEVs
Fc C,W1.60.77
c(C:6, 2.9) (W: 0.49, 1.07) 0.85
Fc C,P5.68c0.31c(C: 2.2, 9.16) (P: 0.09, 0.54) 0.61
Fc C,W,P1.12 0.70c0.04 (C:6.8, 4.5) (W: 0.17, 1.24)
(P:0.2, 0.3)
0.86
Fc (pairwise
difference)
C,W,P0.13 0.72c0.04 (C:0.51, 0.25) (W: 0.53, 0.92)
(P:0.04, 0.13)
0.83
Fcw C,P0.74 0.002 (C: 0.6, 0.88) (P:0.01, 0.007) 0.025
aFc =fuel consumption (l/100 km);Fcw=fuel consumption per 100 kg vehicle weight (l/100 km/100 kg).
bC=regression constant; W=weight coefficient (100 kg); P=power coefficient (10 kW).
cSignificant at the 95% confidence level.
mitigate the effects of high correlation between power and
weight. Here we find that HEVs and ICEVs perform quite
differently. Both weight and power difference are significant
for the HEVs, with a 100 kg weight increase and 10 kW
power increase resulting in 0.4l/100 km and 0.14 l/100 km
increase in fuel consumption, respectively. However, only a
change in weight is a significant predictor of fuel consumption
for the ICEVs, with a 100 kg increase in weight resulting in
a0
.72 l/100 km increase in fuel consumption. Additionally,
the coefficient for power is not significant at the 95% level.
Increasing the sample size of ICEVs to include all engine
options available does not change this result. In order to
confirm our findings we also tested an alternative model using
weight-corrected fuel consumption (Fcw in table 3) to control
for the effect of correlation between weight and power. We
again found that a change in power is a significant predictor of
weight-corrected fuel consumption only for HEVs.
HEVs tend to have lower fuel consumption in urban
driving (with more stop–start driving) than highway driving
due to regenerative braking technology. This is contrary to fuel
consumption findings in conventional vehicles, which have
significantly lower fuel consumption under highway driving
conditions. Therefore we separately analyze fuel consumption
in city and highway driving as a function of weight and
power (table 4). Under city driving conditions, differences
in weight are not a significant predictor of differences in
fuel consumption for HEVs, but power is important. This
is because braking and acceleration are common during city
driving, and the full fuel-saving benefits of hybrid-electric
technology are realized. In contrast, during city driving
weight is a significant predictor of fuel consumption for ICEVs
because conventional technology cannot recover the energy
lost during deceleration. For highway conditions, on the
other hand, differences in weight are a strong determinant of
differences in fuel consumption for both HEVs and ICEVs.
In highway driving mode, both types of vehicle operate
primarily using their internal combustion engine, and hence
differences in weight (rather than peak system power) dictate
fuel consumption.
In summary, the analysis has demonstrated that differ-
ences in fuel consumption between different HEVs are ex-
plained by both weight and power, while for the equivalent
ICEVs they are explained primarily by weight. This is an im-
portant finding: despite the fact that hybrid-electric propulsion
systems use less fuel than conventional internal combustion
engines, heavier and more powerful vehicles are eroding the
fuel consumption benefit. Also, due to the way that hybrid-
electric systems recapture energy during vehicle braking, in-
creased weight is less of a factor in HEVs than in ICEVs.
4. Comparing HEV and ICEV fuel consumption
The share of HEVs in the North American light-duty passenger
vehicle fleet is expected to continue increasing, driven by their
potential for fuel savings and steadily reducing cost. A 2004
study forecasted that HEVs could capture 4–7% of the light-
duty vehicle market by 2008 and 10–15% by 2012 [12]. This
raises the question of how best to estimate the change in fuel
consumption that a given vehicle would realize, were it to use
a hybrid-electric system rather than a conventional engine. We
approach this problem by comparing the set of HEVs against
the sample of equivalent ICEVs, rather than within each set.
We regress fuel consumption differences using three ‘models’
of equivalence between HEVs and ICEVs (table 5).
5
Environ. Res. Lett. 2(2007) 014003 C Reynolds and M Kandlikar
Tab l e 4. Regression analyses results for HEVs and equivalent ICEVs with city and highway fuel consumption (pairwise comparison,
N=36).
Regression coefficients
Predicted variableaPredictor variablesbCW P 95% confidence intervals R2
HEVs
Fc (City) C,W,P0.11 0.15 0.26c(C:0.33, 0.56) (W:0.06, 0.36)
(P: 0.17, 0.34)
0.77
Fc (Highway) C,W,P0.32 0.75c0.02 (C: 0.13,0.53) (W: 0.67, 0.87)
(P:0.06, 0.014)
0.93
ICEVs
Fc (City) C,W,P0.16 0.29c0.26 (C:0.53, 0.68) (W: 0.02,0.61)
(P:0.13, 0.38)
0.65
Fc (Highway) C,W,P0.32 1.21c0.18c(C:0.91, 0.28) (W: 0.9, 1.5)
(P:0.3,0.05)
0.73
aFc =fuel consumption (l/100 km).
bC=regression constant; W=weight coefficient (100 kg); P=power coefficient (10 kW).
cSignificant at the 95% confidence level.
Tab l e 5. Across-group comparison of fuel consumption differences between HEVs and ICEVS. Crepresents the difference in fuel
consumption between HEVs and ICEVs due to the difference in propulsion system technology.
Regression coefficients
Dependent variableaIndependent variablesbCWPConfidence intervals R2
Model 1: Each HEV versus equivalent ICEV (N=9)
Fc C,W3.06c0.5 — (C: 1.68, 4.4) (W:0.48, 1.48) 0.17
Fc C,P2.5c0.1 (C: 1.66, 3.46) (P:0.1, 0.3) 0.17
Fc C,W,P2.8c0.25 0.06 (C: 0.4, 5.2) (W:1.75, 2.26)
(P:0.35, 0.47)
0.18
Model 2: HEV versus ICEV (group comparison N=81)
Fc C,W3.4d0.74d—(C: 3.15, 3.63) (W: 0.67, 0.81) 0.85
Fc C,P2.7d0.30d(C: 2.24, 3.0) (P: 0.25, 0.34) 0.70
Fc C,W,P3.25d0.56d0.1d(C: 3.01., 3.48) (W: 0.45, 0.68)
(P: 0.04, 0.14)
0.87
Model 3: HEV versus ICEV (group comparison with car and SUV sub-groups N=162)
Fc C,W3.3d0.86d—(C: 2.97, 3.7) (W: 0.75, 1) 0.86
Fc C,P2.5d0.32d(C: 2.34, 2.67) (W: 0.3, 0.35) 0.96
Fc C,W,P2.7d0.15c0.27d(C: 2.43, 2.87) (W: 0.02, 0.3)
(P: 0.22, 0.32)
0.97
aFc =fuel consumption (l/100 km).
bC=regression constant; W=weight coefficient (100 kg); P=power coefficient (10 kW).
cSignificant at the 95% confidence level.
dSignificant at the 99% level.
In each model, the dependent variable is the fuel
consumption difference between an HEV and an equivalent
ICEV, and corresponding differences in weight and power
are the independent variables. In each case, the regression
constant, C, is the difference in fuel consumption (in units
of l/100 km) between HEVs and ICEVs. This difference
can be attributed to the effect of using hybrid-electric
technology instead of conventional internal-combustion-
engine technology for the vehicle’s propulsion system. Model
1 is based on the assumption that consumers will switch from
a conventional vehicle to its hybrid counterpart; model 2
allows for any HEV to substitute for any ICEV; and model
3 embeds the assumption that consumers will only switch
from conventional cars to hybrid-electric cars, and likewise
for SUVs. In model 1, each HEV is compared only with its
equivalent (N=9). In model 2, we compare HEVs and
ICEVs as a class, i.e., each HEV was compared with every
ICEV (N=81). In model 3 we split each HEV and ICEV set
into two groups, SUV and cars, and compare all vehicles within
each group (N=45). This is because car and SUV HEVs are
likely to contribute to different relationships between weight,
power and fuel consumption.
6
Environ. Res. Lett. 2(2007) 014003 C Reynolds and M Kandlikar
Equivalence model 1
Only ‘technology’ (i.e. the use of a hybrid-electric propulsion
system rather than an internal combustion engine) was found to
be a significant predictor of the difference in fuel consumption.
On an average, the use of hybrid-electric technology resulted in
a fuel consumption benefit of 2.8l/100 km. Both weight and
power differences were found not to be significant at the 95%
level. The mean differences in power and weight for an HEV
and its ICEV equivalent were small (5% and 9%, respectively),
and the impact of these changes cannot be observed in the
face of substantial differences in fuel consumption. Though
significant, the constant has a large confidence interval and the
model has a low R2(0.18). This suggests wide variation in
the implementation of hybrid technology from model to model,
resulting in large variation in fuel consumption benefits.
Equivalence model 2
When HEVs and ICEVs are compared as a class, the model
shows highly significant results for each of the three predictors
(at the 99% confidence level). An HEV of the same weight and
power uses approximately 3.2l/100 km less fuel than its ICEV
counterpart. Further, an increase in weight of 100 kg results in
a fuel consumption increase of 0.56 l/100 km, and an increase
in power of 10 kW results in a fuel consumption increase
of 0.10 l/100 km. On an average 2007 HEVs are 136 kg
heavier than equivalent ICEVs, resulting in a weight-related
fuel consumption penalty of 0.75 l/100 km. Further, 2007
HEVs have 10 kW more average power than equivalent ICEVs,
resulting in a fuel consumption penalty of 0.1l/100 km. The
total penalty amounts to a reduction in the fuel consumption
benefits of HEVs by 27%.
Equivalence model 3
This model of equivalence allows us to differentiate between
cars and SUVs. Here we find significant effects (at the
95% confidence level) for all three predictors. The average
gain from using hybrid technology was 2.7l/100 km, while
the weight and power penalties were 0.15 l/100 km and
0.27 l/100 km, respectively. This is an interesting result,
because the weight coefficient is almost half the magnitude
of the power coefficient. Compare this result to model 2,
where the weight coefficient is over five times as large as the
power coefficient. The reason for the change in magnitude of
the coefficients is because this model compares like vehicles
with like, and cars are different from SUVs in a number of
important ways. The three hybrid-electric SUVs use all-wheel
drive rather than two-wheel drive, which results in an extra fuel
saving since all of the four wheels provide regenerative braking
capability [7]. Also, SUVs generally have a higher coefficient
of drag than cars and have a larger frontal area.
5. Conclusions
In summary, based on this statistical analysis of 2007 model
year HEVs and their equivalent ICEVs sold in the United
States, this study presents the following conclusions.
(1) Heavier and more powerful hybrid-electric vehicles are
eroding the fuel consumption benefit of this technology.
(2) The fuel consumption penalty imposed by increased
vehicle weight is significantly lower in HEVs than in
equivalent ICEVs. A 100 kg change in vehicle weight
increases fuel consumption by only 0.4l/100 km in
HEVs, compared with 0.7l/100 km in ICEVs.
(3) Three different equivalence models (based on different
comparisons of HEVs against ICEVs) yielded fuel
consumption benefits ranging from 2.7 to 3.25 l/100 km,
with varying effectsof changes in weight and power.
(4) When the HEVs are compared with their ICEV
equivalents (model 3, grouped into cars and SUVs),
the average fuel consumption benefit of an HEV was
2.65 l/100 km. This analysis reveals that an HEV
that is 100 kg heavier than an identical ICEV, holding
everything else constant, has a fuel consumption penalty
of 0.15 l/100 km. Likewise, an HEV that is 10 kW more
powerful than the ICEV results in a fuel consumption
penalty of 0.27 l/100 km.
Hybrid technology is new, and it will evolve as the technology
matures and diffuses within the automobile fleet. We have
shown that, even in the relatively short time that HEVs
have been commercially available, there have been significant
changes in the dimensions, performance and fuel consumption
of the fleet. The number of models available is small, and this
small sample size will be an inevitable challenge for analyses
of the fleet done today. As the number of HEV types increases,
we will no doubt get a more robust picture of the technology.
Acknowledgments
We thank Kimberly Jones for her assistance assembling vehicle
sales and specifications data, and Gordon McTaggart-Cowan
and Julian Marshall for valuable comments on a draft of this
article. The University of British Columbia Bridge Program,
the Natural Science and Engineering Research Council of
Canada, and the Auto21 Network of Centres of Excellence
provided support for this research.
References
[1] An F, Vyas A, Anderson J and Santini D 2001 Evaluating
commercial and prototype HEVs SAE Technical Paper
2001-01-0951
[2] An F, Stodolsky F and Santini D 1999 Hybrid options for
light-duty vehicles SAE Technical Paper 1999-01-2929
[3] Hoffert M I et al 2002 Advanced technology paths to global
climate stability: energy for a greenhouse planet Science
298 981–7
[4] Pacala S and Socolow R 2004 Stabilization wedges: solving the
climate problem for the next 50 years with current
technologies Science 305 968–72
[5] Jackson R B and Schlesinger W H 2004 Curbing the U.S.
carbon deficit Proc. Natl Acad. Sci. 101 15827–9
[6] Romm J 2006 The car and fuel of the future Energy Policy
34 2609–14
[7] An F and Santini D J 2004 Mass impacts on fuel economies of
conventional vs hybrid electric vehicles SAE Trans. 113
258–76
7
Environ. Res. Lett. 2(2007) 014003 C Reynolds and M Kandlikar
[8] An F and Santini D 2003 Assessing tank-to-wheel efficiencies
of advanced technology vehicles SAE Technical Paper
2003-01-0412
[9] Berman B 2006 Hybrid vehicles in the US: available and
expected models available from http://www.hybridcars.com/
cars.html
[10] Heavenrich R M 2006 Light-duty automotive technology and
fuel economy trends: 1975 through 2006 report no.
EPA420-R-06-011, Office of Transportation and Air Quality,
US Environmental Protection Agency
[11] Millikin M 2006 Green car congress: energy, technologies,
issues and policies for sustainable mobility available from
http://www.greencarcongress.com
[12] Greene D L, Duleep K G and McManus W 2004 Future
Potential of Hybrid and Diesel Powertrains in the US
Light-Duty Vehicle Market report no. ORNL/TM-2004/181
(Oak Ridge, TN: Oak Ridge National Laboratory)
[13] US Environmental Protection Agency 2006 Fuel economy
labeling of motor vehicles: revisions to improve calculation
of fuel economy estimates report no EPA420-D-06-002,
Office of Transportation and Air Quality, US Environmental
Protection Agency
[14] Lipman T E and Delucchi M A 2006 A retail and lifecycle cost
analysis of hybrid electric vehicles Transport Res. D
11 115–32
[15] B C Climate Exchange 2005 The hybrid experience report:
Toyota Prius fuel performance available from http://www.
hybridexperience.ca/Toyota Prius Fuel Performance.htm
[16] Santini D, Vyas A D and Anderson J L 2002 Fuel economy
improvement via hybridization vs vehicle performance level
SAE Technical Paper 2002-01-1901
[17] Mansfield E R and Helms B P 1982 Detecting multicollinearity
Am. Stat. 36 158–60
[18] Cook R D 2000 Detection of influential observation in linear
regression Technometrics 42 65–8
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