A national laboratory of the U.S. Department of Energy
Office of Energy Efficiency & Renewable Energy
National Renewable Energy Laboratory
Innovation for Our Energy Future
Cost-Benefit Analysis of
Plug-In Hybrid Electric
Presented at the 22nd International Battery, Hybrid and Fuel Cel
Electric Vehicle Symposium and Exhibition (EVS-22)
October 23–28, 2006
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COST-BENEFIT ANALYSIS OF PLUG-IN HYBRID
ELECTRIC VEHICLE TECHNOLOGY1
National Renewable Energy Laboratory
Plug-in hybrid-electric vehicles (PHEVs) have emerged as a promising technology that uses electricity
to displace petroleum consumption in the vehicle fleet. However, there is a very broad spectrum of
PHEV designs with greatly-varying costs and benefits. In particular, battery costs, fuel costs, vehicle
performance attributes and driving habits greatly-influence the relative value of PHEVs. This paper
presents a comparison of the costs (vehicle purchase costs and energy costs) and benefits (reduced
petroleum consumption) of PHEVs relative to hybrid-electric and conventional vehicles. A detailed
simulation model is used to predict petroleum reductions and costs of PHEV designs compared to a
baseline midsize sedan. Two powertrain technology scenarios are considered to explore the near-term
and long-term prospects of PHEVs. The analysis finds that petroleum reductions exceeding 45% per-
vehicle can be achieved by PHEVs equipped with 20 mi (32 km) or more of energy storage. However,
the long-term incremental costs of these vehicles are projected to exceed US$8,000, with near-term
costs being significantly higher. A simple economic analysis is used to show that high petroleum
prices and low battery costs are needed to make a compelling business case for PHEVs in the absence
of other incentives. However, the large petroleum reduction potential of PHEVs provides strong
justification for governmental support to accelerate the deployment of PHEV technology.
Keywords: Plug-in Hybrid; Hybrid-Electric Vehicles; Battery, Secondary Battery; Modeling,
Simulation; Energy Security.
Introduction to Plug-In Hybrid-Electric Vehicles
Plug-in hybrid-electric vehicles have recently emerged as a promising alternative that uses electricity
to displace a significant fraction of fleet petroleum consumption . A plug-in hybrid-electric vehicle
(PHEV) is a hybrid-electric vehicle (HEV) with the ability to recharge its electrochemical energy
storage with electricity from an off-board source (such as the electric utility grid). The vehicle can
then drive in a charge-depleting (CD) mode that reduces the system’s state-of-charge (SOC), thereby
using electricity to displace liquid fuel that would otherwise have been consumed. This liquid fuel is
typically petroleum (gasoline or diesel), although PHEVs can also use alternatives such as biofuels or
hydrogen. PHEV batteries typically have larger capacity than those in HEVs so as to increase the
potential for petroleum displacement.
Hybrid-Electric Vehicle Terminology
Plug-in hybrid-electric vehicles are characterized by a “PHEVx” notation, where “x” typically denotes
the vehicle’s all-electric range (AER) – defined as the distance in miles that a fully charged PHEV can
drive before needing to operate its engine. The California Air Resources Board (CARB) uses the
standard Urban Dynamometer Driving Schedule (UDDS) to measure the AER of PHEVs and provide
a fair comparison between vehicles . By this definition, a PHEV20 can drive 20 mi (32 km) all-
electrically on the test cycle before the first engine turn-on. However, this all-electric definition fails
1 This work has been authored by an employee or employees of the Midwest Research Institute under Contract
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to account for PHEVs that might continue to operate in CD-mode after the first engine turn-on.
Therefore, the author uses a definition of PHEVx that is more appropriately related to petroleum
displacement. By this definition, a PHEV20 contains enough useable energy storage in its battery to
displace 20 mi (32 km) of petroleum consumption on the standard test cycle. Note that this definition
does not imply all-electric capability since the vehicle operation will ultimately be determined by
component power ratings and their control strategy, as well as the actual in-use driving cycle.
The Potential of Plug-In Hybrid-Electric Vehicles
The potential for PHEVs to displace fleet petroleum consumption derives from several factors. First,
PHEVs are potentially well-matched to motorists’ driving habits – in particular, the distribution of
distances traveled each day. Based on prototypes from the last decade, PHEVs typically fall in the
PHEV10-60 range . Figure 1 shows the US vehicle daily mileage distribution based on data
collected in the 1995 National Personal Transportation Survey (NPTS) . Clearly, the majority of
daily mileages are relatively short, with 50% of days being less than 30 mi (48 km). Figure 1 also
shows the Utility Factor (UF)
curve for the 1995 NPTS data.
Daily Mileage Distribution and Utility Factor Curve
For a certain distance D, the
Utility Factor is the fraction of
Daily mileage distribution
Utility Factor curve
(VMT) that occurs within the first
D miles of daily travel. For a
distance of 30 mi (48 km), the
utility factor is approximately
40%. This means that an all-
electric PHEV30 can displace
equivalent to 40% of VMT,
(assuming the vehicle is fully
recharged each day). Similarly,
an all-electric PHEV60 can
displace about 60%. This low-
daily-mileage characteristic is
Daily Mileage (mi)
why PHEVs have potential to
displace a large fraction of per-
Figure 1: Daily mileage distribution for US motorists based on
vehicle petroleum consumption.
the 1995 National Personal Transportation Survey
However, for PHEVs to displace fleet petroleum consumption, they must penetrate the market and
extrapolate these savings to the fleet level. A second factor that is encouraging for PHEVs is the
success of HEVs in the market. Global hybrid vehicle production is currently several hundred
thousand units per annum . Because of this, electric machines and high-power storage batteries are
rapidly approaching maturity with major improvements in performance and cost having been achieved.
Although HEV components are not optimized for PHEV applications, they do provide a platform from
which HEV component suppliers can develop a range of PHEV components.
Finally, PHEVs are very marketable in that they combine the beneficial attributes of HEVs and battery
electric vehicles (BEVs) while mitigating their disadvantages. Production HEVs achieve high fuel
economy, but they are still designed for petroleum fuels and do not enable fuel substitution/flexibility.
PHEVs, however, are true fuel-flexible vehicles that can run on petroleum or electrical energy. BEVs
do not require any petroleum, but are constrained by battery technologies resulting in limited driving
ranges, significant battery costs and lengthy recharging times. PHEVs have a smaller battery which
mitigates battery cost and recharging time while the onboard petroleum fuel tank provides driving
range equivalent to conventional and hybrid vehicles. This combination of attributes is building a
strong demand for PHEVs, as evidenced by the recently launched Plug-In Partners Campaign .
PHEVs have the potential to come to market, penetrate the fleet, and achieve meaningful petroleum
displacement relatively quickly. Few competing technologies offer this potential combined rate and
timing of reduction in fleet petroleum consumption . However, PHEV technology is not without its
challenges. Energy storage system cost, volume, and life are major obstacles that must be overcome
for these vehicles to succeed. Increasing the battery storage beyond that of HEVs increases vehicle
cost and presents significant packaging challenges. Furthermore, the combined deep/shallow cycling
in PHEV batteries is uniquely more demanding than that experienced by HEVs or BEVs. PHEV
batteries may need to be oversized to last the life of the vehicle, further increasing cost. Given that
HEVs are succeeding in the market, the question relevant to PHEVs is, “What incremental petroleum
reductions can be achieved at what incremental costs?” These factors will critically affect the
marketability of PHEVs through their purchase price and cost-of-ownership. This paper presents the
results of a study designed to evaluate this cost-benefit tradeoff.
Modeling PHEV Petroleum Consumption and Cost
The reduction of per-vehicle petroleum consumption in a PHEV results from two factors:
1. Petroleum displacement during CD-mode, which as previously discussed relates to the PHEVx
designation based on the added battery energy capacity of the vehicle.
2. Fuel-efficiency improvement in charge-sustaining (CS) mode due to hybridization, which relates
to the degree-of-hybridization (DOH) or added battery power capability of the vehicle. HEVs,
which do not have a CD-mode, are only able to realize savings via this second factor.
For a PHEVx, these two factors can be combined mathematically as follows:
PHEVx = [1−UF(x)]
where FCPHEVx is the UF-weighted fuel consumption of the PHEVx, FCCV is the fuel consumption of
the reference conventional (non-hybrid) vehicle and FCCS is the PHEVx’s CS-mode fuel consumption.
Note that this expression becomes approximate for PHEVs without all-electric capability because use
of the utility factor in this way assumes that no petroleum is consumed in the first x miles of travel.
Figure 2 uses Equation 1 to compare the petroleum reduction of various PHEV designs. We see there
are a variety of ways to achieve a target level of petroleum reduction. For example, a 50% reduction is
achieved by an HEV with 50% reduced fuel consumption, a PHEV20 with 30% CS-mode reduction
and by a PHEV40 with 0% CS-mode reduction (this last example is unlikely since PHEVs will show
CS-mode improvement due to hybridization, notwithstanding the increase in vehicle mass from the
larger battery). To demonstrate the
feasible range of CS-mode reduction,
Potential Reduction of Petroleum Consumption in PHEVs
Figure 2 compares several
contemporary HEVs to their
conventional counterparts (in the
case of the Toyota Prius, a
comparison is made to the Toyota
Corolla which has similar size and
performance). At the low end of the
spectrum, the “mild” HEV Saturn
for HEV technology
Vue achieves a modest reduction of
less than 20%. The “full” HEV
Toyota Prius achieves the highest
percentage reduction (40%) of all
HEVs currently on the market
although, in addition to the platform
Reduction in CS-mode Petroleum Consumption (%)
enhancements employed in
Figure 2: Potential per-vehicle reduction of petroleum
production hybrids, it also uses an
consumption in PHEVs
advanced (Atkinson-cycle) engine technology. Note that none of the production HEVs achieve the
50% reduction discussed in the above example, suggesting that there is an upper limit on the benefit of
hybridization alone. Reductions exceeding 50% are available through CD-mode operation in a PHEV,
although increasing PHEVx ranges can be seen to provide diminishing returns due to the nature of the
Utility Factor curve (Figure 1).
The PHEV design space in Figure 2 characterized by CS/CD-mode fuel consumption has a matching
space characterized by battery power/energy. Improving CS-mode fuel consumption implies an
increase in DOH and battery power, while increasing CD-mode benefit implies an increase in PHEVx
and useable battery energy. Moving in either direction incurs additional vehicle costs. However, the
link between battery specifications, CS/CD-mode reductions, and vehicle costs is not obvious and
must be explored through detailed vehicle fuel consumption and cost modeling. Therefore, a model
was developed to predict the petroleum reductions and costs of contrasting PHEV designs compared to
a reference conventional vehicle. The details of this model are presented in the following sections.
Modeling Approach and Scope of the Study
The PHEV cost-benefit model includes several sub-models. First, a performance model calculates
component sizes necessary to satisfy the performance constraints listed in Table 1. Second, a mass
balance calculates the vehicle mass based on component sizes determined by the performance model.
Third, an energy-use model simulates the vehicle’s gasoline and electricity consumption over various
driving cycles. The vehicle performance and energy-use models are coupled to vehicle mass, so the
model is able to capture mass compounding in the sizing of components. Fourth, a cost model
estimates the vehicle retail price based on the component sizes. All costs are reported in 2006 US
dollars. Finally, the results post-processing performs calculations to report the vehicle energy
consumption and operating costs in meaningful ways. The model is implemented in an iterative
Microsoft Excel spreadsheet.
The energy-use model is a detailed, second-by-second, dynamic vehicle model that uses a reverse-
calculation approach . It is also characterized as a power-flow model since it models component
losses/efficiencies as functions of device power, rather than as functions of torque/speed or
current/voltage as in more detailed models. This reverse-calculation, power-flow method provides
rapid estimation of vehicle energy usage and enables the coupled, iterative spreadsheet described
above. A solution is obtained in only a few seconds, meaning that the design space can be explored
very quickly and thoroughly. Several hundred PHEV designs were therefore included in the study.
The model performs simulations of both conventional vehicles (CVs) and HEVs (including PHEVs) so
that side-by-side comparisons can be made. The performance and energy-use models were validated
for a Toyota Camry sedan and Honda Civic Hybrid. In both cases, errors of less than 5% were
observed in the estimates of vehicle performance and energy use.
Two powertrain technology scenarios (Table 2) were included in the study. The near-term scenario
(2005-2010) represents vehicles produced using current-status powertrain technologies, whereas the
long-term scenario (2015-2020) allows for advanced technologies expected to result from ongoing
R&D efforts and high-volume production levels. The long-term scenario does not, however, include
advanced engine technologies since the author wanted to isolate the impact of improved electric drive
and energy storage technologies on the relative cost-benefit of PHEVs.
Vehicle Platform, Performance and Cost Assumptions
All vehicles included in the study satisfied the same performance constraints and used a vehicle
platform identical to the baseline CV. The baseline CV was a midsize sedan (similar to a Toyota
Camry or Chevrolet Malibu) and relevant parameters are presented in Table 1. Most parameters were
calculated from sales-weighted average data for the top selling US midsize sedans in 2003 . Some
parameters, such as rolling resistance, accessory loads, passing acceleration, and gradeability, were
engineering estimates. The baseline manufacturer’s suggested retail price (MSRP) of US$23,392 was
used in combination with the powertrain cost model to estimate the baseline “glider” cost (i.e. vehicle
with no powertrain). The cost of a 121 kW CV powertrain was estimated at US$6,002, leading to an
estimated baseline glider cost of US$17,390.
Table 1: Vehicle Platform and Performance Assumptions for Midsize Sedan
1565 kg (136 kg load)
Gross Vehicle Mass (GVM)
1899 (470 kg load)
Rolling resistance coefficient
Baseline accessory load
800 W elec. (4000 W peak)
0-97 kph (0-60 mph) in 8.0 s
64-97 kph (40-60 mph) in 5.3 s
177 kph (110 mph)
6.5% at 88 kph (55 mph) at GVM
with 2/3 fuel converter power
10.6 / 6.7 / 8.8 L per 100km
(urban / highway / composite)
Table 2: Powertrain Technology Scenarios for the Cost-Benefit Analysis
Twice that of long-term scenario
$/kWh = 11.1 x P/E + 211.1 
$ = ($/kWh + 13) x kWh + 680 
Li-Ion battery design function ,
NiMH battery design function , see Figure 6
see Figure 6
Tray/straps + thermal mgmt = 0.06 kg/kg 
Harness + bus bars = 0.14 kg/kW 
Equivalent circuit model based on P/E ratio,
see Figure 5
SOC design window curve, see Figure 4
Same (assumes Li-Ion cycle life = NiMH)
kg = 21.6 + 0.833 x kW 
kg = 21.6 + 0.532 x kW 
$ = 21.7 x kW + 425 
$ = 16 x kW + 385 
95% peak efficiency curve, see Figure 5
kg =1.62 x kW + 41.8 
$ = 14.5 x kW + 531 
34% peak efficiency curve, see Figure 5
The two things that differentiate a PHEV
from an HEV are the inclusion of a CD
operating mode and a recharging plug.
Therefore, a PHEV can be implemented
using any of the typical HEV
architectures (parallel, series, or power-
split). For this study, a parallel
Figure 3: Parallel HEV powertrain architecture
architecture was assumed with the ability
to declutch the engine from the powertrain (Figure 3). This parallel layout provides greater flexibility
in engine on/off control compared to Honda’s integrated motor assist (IMA) parallel system 
where the engine and motor are always connected. To create more flexibility in engine on/off control,
it was also assumed that all accessories (including air conditioning) would be powered electrically
from the battery.
The battery is the first component sized by the model and the two key inputs are the PHEVx
designation and the battery power-to-energy (P/E) ratio. The useable battery energy is calculated
using an estimate of the vehicle’s equivalent electrical energy consumption per unit distance
multiplied by the target PHEVx distance. The electrical energy consumption is estimated using the
PAMVEC model . The total battery energy is then calculated based on the SOC design window.
Finally, the rated battery power is calculated by multiplying the total battery energy by the input P/E
ratio and then de-rating by 20% to account for battery power degradation at end-of-life.
To achieve similar battery cycle life, different PHEVx ranges require different SOC design windows.
The daily mileage distribution (Figure 1) means that a PHEV10 is far more likely to experience a deep
cycle than a PHEV60. Therefore,
the SOC design window must be
chosen such that the average daily
SOC swing is consistent across the
range of PHEVs. Figure 4 shows
Average daily SOC
swing based on daily
the SOC design windows assumed
Design SOC window
based on PHEVx
in the PHEV cost-benefit model,
based on cycle-life data presented
by Rosenkrantz  and a target
battery life of 15 years (assuming
one full recharge each day). Figure
4 also shows the resulting average
Daily mileage probability distribution
daily SOC swing which is
consistent across the range.
Daily Mileage / PHEVx
Figure 4: SOC design window for PHEVs
The motor power is matched to the battery power, but with the resulting motor power being slightly
smaller after accounting for electric accessory loads and motor/controller efficiency.
Several steps are required to size the engine. First, the required peak power of the engine plus motor is
calculated using the PAMVEC model . This power is typically dictated by the standing
acceleration performance and for the baseline midsize platform is approximately 120kW. The motor
power is then subtracted from the total to provide a requirement for the engine power. This produces
some “engine downsizing,” but there are downsizing limits imposed by other performance constraints.
Continuous performance events (gradeability and top speed) determine the minimum permissible
engine size. Gradeability performance is limited to 2/3 of peak engine power due to engine thermal
management and noise, vibration, and harshness (NVH) considerations. For the baseline midsize
platform, the minimum engine size is approximately 80kW.
Component Efficiencies, Masses, and Costs
Engine and Electric Motor
As discussed in section 2.1, the PHEV energy-use model is a reverse-calculation, power-flow model
that simulates component losses/efficiencies as a function of output power. Both the engine and
electric motor efficiencies are modeled using polynomial expressions for component input power as a
function of output power. The engine curve is based on a 4-cylinder, 1.9L, 95kW gasoline engine. A
3rd-order polynomial was fitted to data from an ADVISOR simulation  using this engine. The
motor curve is based on a 50kW permanent magnet machine and a 9th-order polynomial was fitted to
data from an ADVISOR simulation using this motor. Both efficiency curves are shown in Figure 5.
The engine and motor masses and costs are modeled as linear functions of rated output power. The
engine mass function is derived from a database of 2003 model-year vehicles . The near-term
motor-controller mass function
is based on the 2006 current
Powertrain Components - Normalised Efficiency Curves
status listed in the FreedomCAR
and Vehicle Technologies
Program Plan . The long-
term motor-controller mass is
based on technology 70%
demonstrated in the GM Precept
concept vehicle . The
engine cost function is based on
manufacturers’ data provided to
the EPRI Hybrid-Electric
Vehicle Working Group
(HEVWG) . The near-term
and long-term motor cost
functions are also based on data
Normalised Power (P/Pmax)
reported by EPRI .
Figure 5: Efficiency curves used in the PHEV cost-benefit model
Battery efficiency is modeled using a normalized function for efficiency vs. input power (Figure 5).
This relationship was derived from an equivalent circuit model using realistic values for nominal open-
circuit voltage and internal impedance. Battery-module mass for both NiMH and Li-Ion technology is
modeled using battery design functions developed by Delucchi  and shown in Figure 6. The added
mass of battery packaging and thermal management was also based on .
Battery-module-specific costs ($/kWh) vary as a function of power-to-energy ratio (Figure 6). The
long-term Li-Ion cost curve is based on estimates from EPRI . After speaking with battery
suppliers and other experts, it was estimated that the near-term specific cost of NiMH modules was
approximately double that of EPRI’s long-term prediction. The costs of battery packaging and thermal
management are also based on those listed in .
Recharging Plug and Charger
PHEVs are assumed to be equipped with an inverter-integrated plug/charger with 90% efficiency and
an incremental manufactured cost of US$380 over the baseline inverter cost .
Battery Design Functions
Battery Cost Functions
NiMH (near-term scenario)
LI-ION (long-term scenario)
e Sp 400
Specific Energy (Wh/kg)
Power-to-Energy Ratio (1/h)
Figure 6: Battery design functions and module cost curves assumed for NiMH and Li-Ion technology
Retail Markup Factors
The component cost functions in Table 2 model the manufactured cost of components. To convert
these to retail costs in a vehicle, various markup factors are applied. A manufacturer’s markup of 50%
and dealer’s markup of 16.3% are assumed based on estimates by EPRI 
Powertrain Control Strategy
A generic control strategy was developed for the spectrum of PHEV designs. This control strategy
consists of four basic elements. The basis of the strategy is an SOC-adjusted engine power request:
− k SOC − SOC
t arg et )
When the SOC is higher than the target, the engine power request is reduced to promote CD operation.
Alternatively, when the SOC is lower than the target, the engine power request is increased to recharge
the battery. The adjustment is governed by the factor k which is set proportional to total battery
capacity. An electric-launch speed of 10 mph (16 kph) is also specified, below which the strategy tries
to operate the vehicle all-electrically by setting the engine power request to zero. However, both the
SOC adjustment and electric launch can cause the power ratings of the motor to be exceeded.
Therefore, a third element of the strategy is to constrain the engine power request to within acceptable
limits such that no components are overloaded. Finally, there is engine on/off control logic. The
engine is triggered on whenever the adjusted engine power request becomes positive. Once on,
however, the engine can only turn off after it has been on for at least 5 minutes. This final constraint is
designed to ensure the engine warms up thoroughly so that repeated cold starts are avoided.
The aim of this control strategy is to prioritize discharging of the battery pack. Given the nature of the
daily mileage distribution, this approach ensures that the maximum petroleum will be displaced.
However, the strategy does not explicitly command all-electric operation. Rather, it discharges battery
energy at the limits of the battery/motor power capabilities and uses the engine as needed to
supplement the road load power demand. Therefore, the vehicle behavior that results is totally
dependent on the power ratings of components. Vehicles with higher electric power ratings will have
all-electric capability in more aggressive driving, whereas vehicles with lower electric power ratings
will tend to operate in a “blended” CD-mode that utilizes both motor and engine. For more discussion
of all-electric vs “blended” operation, the reader is directed to .
The cost-benefit model simulates CVs, HEVs, and PHEVs over two cycles – the Urban Dynamometer
Driving Schedule (UDDS) and the Highway Fuel Economy Test (HWFET) – used by the US
Environmental Protection Agency (EPA) for fuel economy and emissions testing and labeling .
Fuel Economy Measurement and Reporting
The PHEV fuel economies and operating costs are measured and reported using a procedure based on
a modification of the Society of Automotive Engineers' (SAE) J1711 Recommended Practice for
Measuring the Exhaust Emissions and Fuel Economy of Hybrid-Electric Vehicles . This
procedure measures the fuel and electricity use in both CD and CS-modes and weights them according
to the Utility Factor (UF), assuming the PHEVs are fully-recharged each day. Further discussion of
this procedure for fuel economy measurement and reporting is provided in .
PHEV2, 5, 10, 20, 30, 40, 50, and 60 vehicles were considered in the study. Also, an HEV0 was
modeled as a PHEV2 with its charger/plug removed. P/E ratios were chosen to vary DOH (defined as
the ratio of motor power to total motor plus engine power) across a range of approximately 10%–55%.
Note that the engine downsizing limit corresponds to a DOH of approximately 32%, and that DOH
higher than this results in excess electric power capability onboard the vehicle.