NREL is a national laboratory of the U.S. Department of Energy, Office of Energy 

Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Contract No. DE-AC36-08GO28308

Integrated Testing, Simulation 

and Analysis of Electric Drive 

Options for Medium-Duty Parcel 

Delivery Vehicles

Preprint

L. A. Ramroth, J. Gonder, and A. Brooker

National Renewable Energy Laboratory 

Presented at the International Battery, Hybrid and Fuel Cell Electric 

Vehicle Symposium 26 (EVS26)

Los Angeles, California

May 6 – 9, 2012

Conference Paper

NREL/CP-5400-53983

September 2012
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1 

EVS26 

Los Angeles, California, May 6-9, 2012

Integrated Testing, Simulation and Analysis of Electric 

Drive Options for Medium-Duty Parcel Delivery Vehicles 

Laurie A. Ramroth, Jeffrey Gonder, Aaron Brooker

National Renewable Energy Laboratory, 1617 Cole Blvd., Golden, CO 80401 

E-mail: laurie.ramroth@nrel.gov 

Abstract

Medium-duty vehicles consume a significant amount of petroleum and emit a large amount of greenhousegases. The National Renewable Energy Laboratory explored pathways to cost effectively reduce that using 

gasoline and diesel plug-in hybrid electric vehicles. The analysis started by verifying diesel-conventional 

and diesel-hybrid parcel delivery vehicle models. These plug-in hybrid variants were then run on a fielddata-derived design matrix to analyze the effect of drive cycle, distance, battery replacements, battery 

capacity, and motor power on fuel consumption and lifetime cost. Using two scenarios representing 2011 

and 2030 fuel and battery prices, plug-in hybrid lifetime costs are compared with diesel conventional 

lifetime costs. Under a future cost scenario of $100/kWh battery energy and $5/gal fuel, plug-in hybrids are 

cost effective. Assuming a current cost treatment of $700/kWh and $3/gal fuel, however, they rarely recoup 

the additional motor and battery cost with fuel cost savings. The results also highlight the importance of 

understanding the application’s drive cycle, daily driving distance, and kinetic intensity. For those instances 

in the current cost scenario where the additional plug-in hybrid cost is regained in fuel savings, the 

combination of kinetic intensity and daily distance travelled does not coincide with the usage patterns 

observed in the field data. If the usage patterns were adjusted they could possibly become cost effective. 

This study did not include potential improvements from reduced brake maintenance due to regenerative 

braking in its cost analysis.

Keywords: Medium-duty, HEV, PHEV, simulation, drive cycles, duty cycles

1 Introduction

Medium-duty vehicles consume a significant 

amount of petroleum and emit a large amount of 

greenhouse-gases. Medium-duty vehicles are 

typically identified as classes 3–6 and weigh 

between 4,536 and 11,793 kg (10,001–26,000 

lbs). Medium-duty vehicles in the parcel-delivery 

vocation are ideal candidates for electric drive 

trains because they typically share the following 

characteristics:

• Route predictability

• Daily drive cycles that return to a central 

depot, facilitating overnight charging
2 

• Stop-and-go drive cycles that allow for 

the capture of energy from regenerative 

braking

• More focus on total cost of ownership as 

opposed to capital cost

2 Approach

2.1 Fuel Consumption Measurement 

and Model Verification

Two parcel delivery vehicles owned and operated 

by the United Parcel Service were transported to 

the National Renewable Energy Laboratory’s 

(NREL’s) Renewable Fuels and Lubricants 

(ReFUEL) research laboratory for fuel economy 

and emissions testing on the chassis 

dynamometer. Both the conventional and hybrid 

diesel vehicle used the same 149-kW engine. The 

hybrid-electric van was equipped with a parallelhybrid system from the Eaton Corporation. The 

vehicles were tested at the ReFUEL laboratory 

on three cycles—the New York Composite Cycle 

(NYComp), the Heavy Heavy-Duty Diesel Truck 

(HHDDT), and the Hybrid Truck Users Forum 

(HTUF) 4.

The models were developed in NREL’s Future 

Automotive System Technology Simulator 

(FASTSim). FASTSim uses vehicle 

characteristics, basic component specifications, 

and engine-specific efficiency data to represent a 

vehicle. It simulates the vehicle as it travels 

through a time versus speed drive cycle. The 

model captures key aspects including 

regenerative braking, energy management 

strategies, and auxiliary loads.

Table 1: Vehicle and component specifications

Conventional 

Diesel

Diesel Hybrid

Test Weight 6,813 kg 7,303 kg

Aerodynamics

 Drag 

 Frontal Area

0.7

7.80 m2

0.7

7.80 m2

Wheels

 Rolling Resistance

 Radius

0.008

0.419 m

0.008

0.419 m

Battery

 Energy

 Power 

N/A 

N/A 

1.8 kWh

Matched to 

Motor

Engine

 Power 149 kW 149 kW

Motor

 Peak Continuous Power 

 Peak Power

N/A 

N/A

26 kW

44 kW

Accessory 

 Power 3 kW 1.22 kW

The model matched data reasonably well. In 

Figure 1, the grey error bars represent 10% 

variability in the ReFUEL laboratory’s measured 

results. Each model result fell within the bars. The 

simulated hybrid results show more variance than 

the conventional results, but still fall within 10% 

of the measured results.

Figure 1: Model verification

The primary source of uncertainty in the hybrid 

model lies in the motor-efficiency map. 

Component data for the motor were unavailable. 

The model uses a motor-efficiency map from 

another vehicle and assumes a peak efficiency of 

93%.

The engine efficiency map for the conventional 

model was created from ReFUEL laboratory test 

data and a maximum-torque curve from the engine 

manufacturer. 

2.2 Plug-in Hybrid Model Development

The diesel conventional is used as a point of 

reference for the other powertrain/fuel 

combinations in the cost and fuel-use analyses.

The diesel hybrid has the same engine as the diesel 

conventional. A plug-in hybrid version of the 

model was developed based on the hybrid-diesel 

template.

To make the plug-in hybrid electric vehicles 

(PHEV) comparable, the NREL team applied 

similar vehicle-specific parameters and matched 

the engine power to that of the diesel hybrid and 

conventional (149 kW). The engine power was 

0 

2 

4 

6 

8 

10 

12 

14 

Fuel Economy (mpg)

ReFUEL Measurement

Simulation Result

0

2

4

6

8

10

12

14

Fuel Economy (mpg)

ReFUEL Measurement

Simulation Result
3 

held constant to ensure enough power for long 

hill climbs. Acceleration is typically used to 

identify two vehicles as comparable; however, 

for the parcel-delivery vocation we assume that 

fleet managers are primarily concerned with fuel 

economy and improving their bottom line.

The mass of the diesel and gasoline plug-in 

hybrid is based on the mass of the diesel hybrid 

with an appropriate adjustment for the additional 

battery capacity. No adjustment was made for the 

gasoline hybrid—the diesel hybrid and gasoline 

hybrid were assumed to be of the same mass. 

Battery power was matched to motor power 

through motor efficiency. To be consistent with a 

previous study, the NREL team assumed a 

starting battery capacity of 2.5 kWh [1]. The 

plug-in hybrid model used the diesel-hybrid 

accessory load. 

2.3 Field Data Framing the Analysis 

Field data played an important role in the 

analysis. The NREL Fleet Test and Evaluation 

team is building a fleet data center of field drive 

cycle and performance data. A subset of this data 

was chosen because it was recorded using 

ISAAC loggers and appeared to have the best 

data quality of the group. It is also one of 

NREL’s most recent projects. For this subset, 

over a month of drive cycle data was collected 

for 11 vehicles instrumented with GlobalPositioning System-enabled data loggers. This 

field data framed the selection of the design 

matrix. Although several metrics, including daily 

distance traveled and kinetic intensity, were 

measured (e.g., average speed, stops/km, and 

accelerations/decelerations) and evaluated for 

consistency, of particular importance was daily 

vehicle distance traveled and kinetic intensity 

[2]. 

The route predictability of parcel delivery fleet 

vehicles makes them ideal candidates for 

electrification. The electric drive train can be 

designed to optimize cost specific to the load and 

daily distance traveled. A density plot of daily 

distance traveled illustrates where the design 

space (40–160 km) falls in relation to the field 

data collected (Figure 2). The design space 

envelops the daily distances traveled by these 

vehicles fairly well.

Figure 2: Comparison of daily distance traveled design 

space with field data

Kinetic intensity, a metric that is derived from the 

road-load equation for power, is linked to the 

magnitude and frequency of accelerations, and as 

such, offers insight into the cycle-specific benefits 

of adding an electric drive. A kernel density plot of 

kinetic intensity illustrates where the selected 

standard cycles fall in relation to the kinetic 

intensities measured in the field (Figure 3). The 

HTUF 4 drive cycle was selected as the standard 

drive cycle that best approximated the routes 

measured in the field, while the Orange County 

Bus (OC Bus) and Urban Dynamometer Driving 

Schedule Heavy-Duty (UDDS HD) cycles were 

selected as the upper and lower boundaries for 

vocational kinetic intensity. The density plot of the 

field data shows a bimodal distribution with the 

HTUF 4 cycle’s kinetic intensity corresponding to 

the first mode/peak.

Figure 3: Comparison of kinetic intensities for field and 

stock drive cycles
4 

2.4 Design and Cost Matrix 

Figure 2 and Figure 3 lead to the development of 

the design matrix in Table 2. To ensure 

commercial availability of the battery, the powerto-energy ratio was set at a floor of 1.125.1 The 

battery power was held constant at 30 kW unless 

the power-to-energy ratio fell below the 1.125 

limit. If the ratio fell below this limit, the battery 

power was increased to compensate. A set of 

simulations is run at a motor power matched to 

the 30-kW battery power. Another set of 

simulations is run matching the motor power to 

the varied battery power.

Table 2: Design matrix for PHEVs

Drive cycles UDDS HD, HTUF 4, OC 

Bus

Daily distance traveled 40, 80, 120, 160 km

Additional battery 

capacity

10, 20, 40, 60 kWh

Battery power MAX (30 kW, 

Capacity×P/E) 

Battery power-to-energy 

ratio

1.1252

Two cost scenarios were developed to represent a 

fair range of costs. Current and future fuel and 

electricity costs are yearly highs for 2011 and 

2030, respectively [3]. Long-term battery cost 

per kilowatt-hour is cited from the United States 

Advanced Battery Consortium (USABC) Goals 

for Advanced Batteries for EVs [4]. Current 

battery cost per kilowatt-hour is cited from the 

U.S. Department of Energy [5]. 

Table 3: Cost matrix

Reference Key

USABC/DOE

EIA

Cost/Scenario Current Future

Battery Cost $700/kWh $100/kWh

Fuel Cost

 Gas 

 Diesel

$0.81/L ($3.08/gal)

$0.85/L ($3.23/gal)

$1.29/L ($4.90/gal)

$1.37/L ($5.19/gal)

Electricity Cost $0.11/kWh $0.11/kWh

In addition to this cost matrix, a diesel engine 

credit was applied to the gasoline plug-in hybrid 

to compare it with the diesel conventional 

baseline. Battery replacement, lifetime 

electricity, and lifetime fuel use were discounted 

to make costs comparable in present day dollars.

 

1 Smith Newton P/E ratio.

2 Smith Newton battery

Additional assumptions are listed in Table 4. The 

referenced battery targets were manipulated into a 

form compatible with FASTSim. 

Table 4: Additional assumptions

Vehicle life (years) 15

Motor and 

controller cost

$21.7/kW + $425

Markup factor 1.75

Discount rate 8%

Charger efficiency 0.9

2.5 Battery-Life Model and 

Replacements

Battery life and replacements were estimated using 

cycle-wear data from Johnson Controls, as shown 

in Figure 4. The curve labeled ―Original‖

represents data published by Johnson Controls. 

These data were obtained at the cell level and do 

not capture variations in calendar-life, temperature, 

or power-level on life. To help account for those 

impacts, the ―Today’s Adjusted‖ curve was 

created by adjusting the ―Original‖ case to match 

published data for the Nissan LEAF and the Chevy 

Volt battery life expectations [6]. 

Figure 4: Battery Cycle Life Curves

By solving for the number of cycles (x) and 

plugging in the state-of-charge (SOC) swing (y) 

the model can calculate the percent wear for every 

charge fluctuation.

3 Results

This section presents analytical results for the 

specified range of vehicle configuration, usage, 

and economic scenarios.
5 

3.1 Cumulative Fuel Consumption vs. 

Daily Vehicle Miles Traveled

The effects of battery capacity, motor power, fuel 

energy density, and battery replacement on fuel 

consumption for plug-in hybrids are illustrated in

Figure 5 – Figure 8. 

Effect of increasing battery capacity (Figure 

5). Increasing battery capacity increases the 

distance traveled in charge depleting mode. In 

Figure 5 increasing color intensity corresponds to 

increasing battery energy. The higher the battery 

capacity, the greater the distance traveled in 

charge depleting mode.

The charge-depleting and charge-sustaining 

mode of vehicle operation can be identified from 

the fuel consumption vs. daily distance traveled 

plots. The vehicle starts off in charge-depleting 

mode, only using the engine if the battery alone 

cannot meet the power demand. Once the battery 

depletes, the upward slope indicates chargesustaining mode. It plateaus as greater amounts 

of travel are done in charge sustaining mode.

An expanded matrix of daily distances traveled is 

plotted in the cumulative fuel consumption plots. 

The grayed-out portions of the plot illustrate 

those areas that were not included in the cost 

design matrix.

Figure 5: Effect of increasing battery capacity

Effect of increasing motor power to match 

battery power (Figure 6). Two sets of 

simulations were run. One set of simulations was 

run with a motor power matched to the 30-kW 

battery power. Another set of simulations was 

run matching the motor power to the varied 

battery power. A higher-power motor can 

provide the excess power that would have 

otherwise been supplied by the engine.

Increasing the motor power on the 42.5-kWh 

(power 47.8 kW) and 62.5-kWh (power 70.3 kW) 

batteries—where the battery power-to-energy ratio 

is fixed at 1.125—results in significantly lower 

fuel consumption in charge-depleting and slightly 

lower fuel consumption in charge-sustaining mode.

In Figure 6, Figure 7, and Figure 8 the text box 

corresponds to the change illustrated by the dotted 

lines. In Figure 6 dotted lines represent those 

simulations run with the motor power matched to 

the varied battery power while solid lines represent 

the motor power matched to the 30-kW battery 

power.

Figure 6: Effect of increasing motor power to match 

battery power

Effect of decreasing energy density (Figure 7). 

Dotted lines represent the gasoline-fueled plug-in 

hybrid while solid lines represent the diesel-fueled 

plug-in hybrid. The gasoline plug-in vehicle has 

slightly higher fuel consumption in chargedepleting mode and significantly higher fuel 

consumption in charge-sustaining mode.

Figure 7: Effect of decreasing energy density of fuel
6 

Effect of battery replacement (Figure 8). Sets 

of simulations were also run with and without 

battery replacement. Adding a battery 

replacement results in a larger useable 

capacity/SOC window—illustrated in the plots 

by an extension of the charge-depleting operating 

mode. Expanding the usable SOC window allows 

the powertrain to use the battery more which

saves fuel and increases wear.

Figure 8: Effect of battery replacement

3.2 Lifetime Cost Analysis

Three different methods compare costs: a relative 

comparison with the baseline diesel 

conventional, a component-level comparison, 

and a fuel savings comparison. The relative 

comparison subtracts the cost of the baseline 

diesel conventional (fuel) from the cost of the 

plug-in hybrid version (battery and motor, fuel, 

and electricity). The component-level 

comparison charts allow for easy identification of 

the cost makeup in terms of traction battery and 

motor, liquid fuel, electricity, and replacement 

battery. Lastly, the fuel savings comparison 

enables determination of how many liters of 

diesel fuel were saved by the plug-in hybrid 

gasoline or diesel vehicle when compared to the 

diesel conventional as well as the amount spent 

or saved to save one liter of diesel fuel.

3.2.1 Vehicle Nomenclature

Column charts (Figure 10 - Figure 16) are 

organized by daily distance traveled, vehicle 

configuration and battery capacity, kinetic 

intensity of drive cycle, battery replacement, and 

motor power, in that order as applicable.

The labels represent the configuration. The first 

set of labels—UDDS HD, HTUF 4, and OC 

Bus—show results for the conventional diesel 

vehicle. The subsequent sets of labels are in order 

of increasing battery capacity for the plug-in 

hybrid configurations; i.e., UDDS HD + 10, HTUF 

4 + 10, and OC Bus + 10 represent the plug-in 

hybrid configuration with a 12.5-kWh battery 

capacity.

It should be noted that the +40 and +60 kWh 

scenarios resulted in a battery power-to-energy 

ratio of less than 1.125. For these cases the battery 

power was increased and two sets of motor power 

simulations were run: one with a motor power 

matched to the original 30-kW battery power and 

another with the motor power matched to the 

varied battery power. In the column charts this is 

shown in two instances of each cycle. The first 

instance corresponds to the constant-power 

scenario while the second corresponds to the 

varied motor power scenario.

3.2.2 When Are Plug-In Hybrids Cost 

Effective? 

Figure 10 - Figure 13 represent the difference 

between the plug-in hybrid lifetime cost and the 

diesel conventional lifetime cost. The plug-in 

hybrid lifetime cost is composed of upfront battery 

and motor costs, liquid fuel cost, electricity cost, 

and a battery replacement cost as applicable. The 

diesel conventional lifetime cost is composed of 

the cost of liquid fuel. A positive value indicates 

that the plug-in hybrid is more expensive.

Assuming $700/kWh battery costs and $3/gal fuel 

costs, there were very few usage patterns in which 

the plug-in hybrid paid off. Several observations 

can be made from these graphs. For each battery 

capacity the cycle with the highest kinetic intensity 

paid off first. Figure 10 and Figure 11 show the 

scenarios that paid off for the plug-in hybrid 

diesel, with and without replacements. For most 

battery sizes, the costs were not recouped with 

current-scenario cost assumptions. There were a 

few cases, however, where the plug-in hybrid costs 

were recouped. When a vehicle exceeded 160 

km/day the 12.5-kWh battery paid back on all 

cycles. For those vehicles that travel distances 

greater than 160 km/day (Figure 2) on a cycle with 

high kinetic intensity, there is a potential for 

$10,000 in savings. In general, the higher motor 

power was advantageous on those usage scenarios 

that exceeded 80 km daily distance traveled and 

ran on drive cycles of higher kinetic intensity (i.e., 

HTUF 4 and OC Bus). The higher motor power
7 

was not advantageous in the columns marked 

with an “X.”

Figure 9 focuses on the cost effectiveness of a 

12.5-kWh diesel plug-in hybrid with no battery 

replacement under the current cost scenario. 

Under the current cost scenario of $700/kWh and 

$3/gal fuel, diesel plug-in hybrids seldom recoup 

the additional motor and battery cost. In those 

instances where the additional cost is regained in 

fuel savings (the region of the figure marked with 

a transparent white overlay), the kinetic intensity 

and daily distance traveled do not coincide with 

the usage patterns observed in the field data. If 

the usage patterns were adjusted, there is a 

potential for the plug-in hybrids to become cost 

effective.

Figure 9: Usage patterns and cost effectiveness of a 

12.5 kWh diesel plug-in hybrid with no battery 

replacement under the current cost treatment

The gasoline plug-in hybrid vehicle did not pay 

off with or without battery replacements in the 

current scenario.

Figure 12 and Figure 13 show the cases that paid 

off for the plug-in hybrid diesel, with and 

without replacements, in the future scenario. All 

were cost effective except the 62.5 kWh battery 

case with the lower motor power and battery 

replacement when going 40 km per day on the 

least kinetically intense cycle.

3.2.3 Cost Breakdown

A stacked column chart aids in understanding 

how these costs add up. In the stacked column 

charts, battery replacements are easily 

identifiable by the battery replacement cost. 

Figure 14 illustrates the cost breakdown for the 

diesel plug-in hybrid vehicle operated 160 

km/day under the current scenario. It agrees with 

the results in Figure 10 and Figure 11. For the 

12.5-kWh battery, all the scenarios without a 

battery replacement paid back (relative to the 

lifetime fuel cost for the conventional vehicle over 

the corresponding cycle). For scenarios with a 

battery replacement, only the OC Bus paid back.

3.2.4 Cost Effectiveness

One of the benefits of adding an electric drive train 

is fuel savings. In Figure 15 and Figure 16, fuel 

savings and cost effectiveness are plotted for the 

above scenarios. The scenarios where the PHEV 

was less expensive than the diesel conventional are 

identified by a negative cost per liter saved. As 

expected, the longer the distance traveled, the 

greater the fuel savings and the lower the cost per 

liter saved.

4 Conclusion

This study evaluated a gasoline and a diesel plugin hybrid vehicle to determine when a plug-in is a 

good value in comparison to a conventional diesel 

parcel delivery vehicle. The future scenario shows 

that plug-in hybrids become cost effective when 

battery costs meet USABC’s long-term goals for 

advanced batteries for electric vehicles 

($100/kWh) and fuel reaches $5/gal. Under the 

current cost scenario with an assumption of 

$700/kWh battery energy and $3/gal fuel, PHEVs 

are generally not cost effective.

This study also evaluated battery replacements and 

higher motor power in terms of cost. Replacing the 

battery was not cost effective unless battery costs 

go down. A higher motor power was cost effective 

in those scenarios that included a battery 

replacement, or in those cases with no replacement 

where the drive cycle was kinetically intense and 

traveled enough miles to recoup the extra cost 

through hybridization fuel savings (from 

regenerative braking, etc.).

The results show that kinetic intensity and distance 

traveled are important considerations when trying 

to evaluate if a plug-in hybrid vehicle is a good 

investment. Under the current scenario with no 

battery replacement, the plug-in hybrids that were 

cost effective traveled distances exceeding 160 km 

per day to pay off the additional 12.5-kWh battery 

cost on the UDDS HD, HTUF 4, and OC Bus 

cycles. For these simulations, the cost savings is 

greatest on the most kinetically intense cycle, the 

OC Bus cycle.
8 

There are several possible directions for future 

work. They include evaluating the threshold of 

where PHEVs become cost effective, 

incorporating thermal and calendar battery wear 

into the model, and evaluating total cost of 

ownership. This study does not include a hybrid 

discount for brake maintenance costs. The Fleet 

Testing and Evaluation Team observed roughly a 

doubling of brake life on most fleets. These 

modifications could change the results of this 

study.
9 

Figure 10: Current scenario, no replacement, diesel PHEV

Figure 11: Current scenario, replacement, diesel PHEV

Figure 12: Diesel PHEV, future scenario, no replacement

Figure 13: Diesel PHEV, future scenario, replacement

-20

-10

0

10

20

30

40

50

60

70

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC Bus + 60OC Bus + 60

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC Bus + 60OC Bus + 60

Delta Lifetime Costs Thousands

120 km/day 160 km/day

-20

0

20

40

60

80

100

120

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC Bus + 60OC Bus + 60

Delta Lifetime Costs Thousands

160 km/day

-60

-50

-40

-30

-20

-10

0

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC Bus + 60OC Bus + 60

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC Bus + 60OC Bus + 60

Delta Lifetime Costs

Thousands

40 km/day 160 km/day

-60

-50

-40

-30

-20

-10

0

10

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC Bus + 60OC Bus + 60

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC B 60

Delta Lifetime Costs

Thousands

40 km/day 160 km/day
10 

Figure 14: Diesel PHEV, current scenario

Figure 15: Diesel PHEV, no replacement

Figure 16: Diesel PHEV, replacement

0

50

100

150

200

250

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10UDDS HD + 10

HTUF 4 + 10HTUF 4 + 10

OC Bus + 10OC Bus + 10

UDDS HD + 20UDDS HD + 20

HTUF 4 + 20HTUF 4 + 20

OC Bus + 20OC Bus + 20

UDDS HD + 40UDDS HD + 40UDDS HD + 40

UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40OC Bus + 40OC Bus + 40

UDDS HD + 60

UDDS HD + 60UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60HTUF 4 + 60HTUF 4 + 60

OC Bus + 60OC Bus + 60OC Bus + 60OC Bus + 60

Lifetime Costs 

Thousands

Upfront Battery and Motor Electricity Fuel Replacement Battery

160 km/day

0

10

20

30

40

50

60

70

80

90

100

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40

OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC Bus + 60OC Bus + 60

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC Bus + 60OC Bus + 60

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC Bus + 60

OC Bus + 60

15-year Liters Saved

Thousands

15-year liters saved $/L saved (current) $/L saved (future)

40 km/day 120 km/day 160 km/day

-1

0

1

2

3

4

5

6

7

8

9

0

10

20

30

40

50

60

70

80

90

100

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC Bus + 60OC Bus + 60

UDDS HD

HTUF 4

OC Bus

UDDS HD + 10

HTUF 4 + 10

OC Bus + 10

UDDS HD + 20

HTUF 4 + 20

OC Bus + 20

UDDS HD + 40UDDS HD + 40

HTUF 4 + 40HTUF 4 + 40

OC Bus + 40OC Bus + 40

UDDS HD + 60UDDS HD + 60

HTUF 4 + 60HTUF 4 + 60

OC Bus + 60OC Bus + 60

$/L saved

15-year Liters Saved

Thousands

15-year liters saved $/L saved (current) $/L saved (future)

40 km/day 160 km/day
11 

Acknowledgments

The authors respectfully acknowledge the 

contributions of the National Renewable Energy 

Laboratory’s Renewable Fuels and Lubricants 

and Fleet Test and Evaluation team. Their work 

was essential to this analysis. The authors 

gratefully acknowledge the programmatic 

support of the U.S. Department of Energy, Office 

of Energy Efficiency and Renewable Energy, 

Vehicle Technologies Program. The authors 

particularly wish to thank Vehicle Systems 

activity managers David Anderson and Lee 

Slezak for their guidance and support.

References

[1] R. A. Barnitt et al., 2010, “Model-based 

analysis of electric drive options for 

medium-duty parcel delivery vehicles,”

National Renewable Energy Laboratory, 

Golden, CO, Conference Paper NREL/CP5400-49253. 

[2] O'Keefe, M., Simpson, A., Kelly, K., and 

Pedersen, D., “Duty Cycle Characterization 

and Evaluation Towards Heavy Hybrid 

Vehicle Applications,” SAE Technical 

Paper 2007-01-0302, 2007, 

doi:10.4271/2007-01-0302. 

[3] U. S. Energy Information Administration, 

Annual Energy Outlook, 2011,

http://www.eia.gov/oiaf/aeo/tablebrowser/a

eo_query_server/?event=ehExcel.getFile&st

udy=AEO2011®ion=1-

0&cases=ref2011-d020911a&table=3-

AEO2011&yearFilter=0, accessed on 2012-

01-18. 

[4] United States Council for Automotive 

Research LLC, USABC Goals for Advanced 

Batteries for EVs,

http://www.uscar.org/guest/view_team.php?

teams_id=11, accessed on 2012-01-18. 

[5] Howell, D., Hybrid Electric Systems, United 

States Department of Energy,

http://www1.eere.energy.gov/vehiclesandfu

els/pdfs/merit_review_2011/plenary/vtpn07

_howell_ft_2011_o.pdf, accessed on 2012-

01-18. 

[6] M. O’Keefe et al., 2011, “Battery 

Ownership Model: A Tool for Evaluating 

the Economics of Electrified Vehicles and 

Related Infrastructure,” National 

Renewable Energy Laboratory, Golden, 

CO, Conference Paper NREL/CP-5400-

49127. 

Authors

Laurie Ramroth

National Renewable Energy 

Laboratory 

Golden, CO USA

Email: laurie.ramroth@nrel.gov

Ms. Ramroth is an Engineer at NREL. 

She holds a B.S. in mechanical 

engineering from Wayne State University in Detroit, 

Michigan, where she focused on alternative energy 

technologies.

Jeffrey Gonder

National Renewable Energy 

Laboratory 

Golden, Colorado USA 

Email: jeff.gonder@nrel.gov

Mr. Gonder is a Senior Engineer at 

NREL’s Center for Transportation 

Technologies and Systems. He holds a B.S. in 

Mechanical Engineering from the University of 

Colorado and an M.S. in Mechanical Engineering from 

Pennsylvania State University. His research activities 

include both simulation and hardware testing of 

conventional, hybrid, plug-in and fuel cell vehicles.

Aaron Brooker

National Renewable Energy Laboratory 

Golden, CO USA

Email: aaron.brooker@nrel.gov

Mr. Brooker is a Senior Engineer at 

NREL. He holds a B.S. in mechanical 

engineering from Michigan 

Technological University and an M.S. in mechanical 

engineering from the University of Colorado.