____________________________________ 

NREL/CP-5400-60053. Posted with permission. 

Presented at the SAE 2013 Commercial Vehicle 

Engineering Congress. 

2013-01-2471 

Published 09/24/2013

doi:10.4271/2013-01-2471

saecomveh.saejournals.org 

Overcoming the Range Limitation of Medium-Duty Battery

Electric Vehicles through the use of Hydrogen Fuel-Cells
	

Eric Wood, Lijuan Wang, Jeffrey Gonder, and Michael Ulsh
	

National Renewable Energy Laboratory
	

ABSTRACT 

Battery electric vehicles possess great potential for decreasing lifecycle costs in medium-duty applications, a market 

segment currently dominated by internal combustion technology. Characterized by frequent repetition of similar routes and 

daily return to a central depot, medium-duty vocations are well positioned to leverage the low operating costs of battery 

electric vehicles. Unfortunately, the range limitation of commercially available battery electric vehicles acts as a barrier to 

widespread adoption. This paper describes the National Renewable Energy Laboratory's collaboration with the U.S. 

Department of Energy and industry partners to analyze the use of small hydrogen fuel-cell stacks to extend the range of 

battery electric vehicles as a means of improving utility, and presumably, increasing market adoption. This analysis 

employs real-world vocational data and near-term economic assumptions to (1) identify optimal component configurations 

for minimizing lifecycle costs, (2) benchmark economic performance relative to both battery electric and conventional 

powertrains, and (3) understand how the optimal design and its competitiveness change with respect to duty cycle and 

economic climate. It is found that small fuel-cell power units provide extended range at significantly lower capital and 

lifecycle costs than additional battery capacity alone. And while fuel-cell range-extended vehicles are not deemed 

economically competitive with conventional vehicles given present-day economic conditions, this paper identifies 

potential future scenarios where cost equivalency is achieved. 

CITATION: Wood, E., Wang, L., Gonder, J., and Ulsh, M., "Overcoming the Range Limitation of Medium-Duty Battery
	

Electric Vehicles through the use of Hydrogen Fuel-Cells," SAE Int. J. Commer. Veh. 6(2):2013, doi:10.4271/2013-01-2471.
	

BEV and a battery price of $600/kWh, adding range with INTRODUCTION 

batteries alone increases the capital cost of the vehicle by Battery electric vehicles (BEVs) possess great potential $600/mi (and this is before accounting for increasing the curb for decreasing lifecycle costs in medium-duty applications, a weight of the vehicle with additional batteries). With the market segment currently dominated by internal combustion present-day capital cost of BEVs already significantly higher technology. Characterized by frequent repetition of similar than CVs, the notion of increasing vehicle range exclusively routes and daily return to a central depot, medium-duty through electrical energy storage is difficult to justify. vocations are well positioned to leverage the low operating As an alternative to increasing battery size, the utility of costs of BEVs. BEVs could be improved through the use of an on-board Unfortunately, the range limitation of commercially generator that produces electricity to supplement the battery available BEVs acts as a barrier to widespread adoption. pack as it nears depletion. This arrangement could allow the Unlike conventional vehicles (CVs), BEVs are constrained by vehicle to leverage the low operating costs of grid electricity long recharge times and a lack of ubiquitous access to public for the majority of miles traveled while having the capability refueling stations. Consequently, the BEV market is limited to utilize a higher cost fuel for range extension when to vocations where planned routes will rarely (if ever) exceed necessary. the fully charged driving range of the vehicle. For this analysis, we will focus on a hydrogen fuel cell as Overcoming this range dilemma with batteries alone the range-extending hardware of choice. By employing proves problematic due to the high capital cost associated hydrogen as a range extending fuel, the vehicle can retain with electrical energy storage. For example, assuming an zero-emissions capability as well as the potential for electric consumption rate of 1 kWh/mi for a medium-duty operation using 100% renewably generated energy. Herein 

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we will refer to such a powertrain arrangement as a fuel-cell 

range-extended vehicle (FC-REV). 

The design space for a FC-REV quickly becomes 

complicated as the merits of battery capacity and fuel-cell 

power are pitted against one another. A singular range 

requirement could be satisfied using a number of different 

hardware configurations ranging from a capital cost intensive, 

battery-dominant design to an operating cost intensive, fuel 

cell-dominant design. The design space is further expanded 

by considering at what point during the depletion of the 

battery to engage the fuel cell. While many hardware/ 

software combinations capable of meeting a given range 

requirement exist, exploring the design space to identify a 

cost-optimal solution is a non-trivial task. The following 

section outlines a methodology for identifying cost-optimal 

FC-REV designs given inputs such as duty cycle, component 

costs, and energy costs. 

VEHICLE MODELING 

Modeling Environment 

All vehicle modeling done in this analysis was performed 

using the National Renewable Energy Laboratory's (NREL's) 

Future Automotive Systems Technology Simulator 

(FASTSim) [1]. FASTSim is a vehicle simulation tool 

developed by NREL to evaluate the impact of various 

technologies on vehicle performance, cost, and utility in 

conventional and advanced technology powertrains. 

Operating in the Excel/ Visual Basic environment, FASTSim 

calculates the power necessary to meet a given speed trace 

while considering component limitations, system losses, and 

auxiliary loads. 

The baseline BEV model considered in this analysis was 

calibrated to real-world on-road data from a Smith Newton 

parcel delivery vehicle using the vehicle attributes and 

component sizes shown in Table 1 [2]. The simulated error in 

electricity consumption between simulation results and realworld data of <2% is used as justification for extrapolating 

this model in parametric studies. 

Table 1. Baseline vehicle attributes and component sizes 

used to model the Smith Newton medium-duty BEV. 

Operating Philosophy 

Three energy management strategies were considered, as 

shown in Figure 1. Figure 1a shows the “traditional” charge 

depleting (CD) battery operation followed by charge 

sustaining (CS) operation (where the battery charge is 

sustained at a steady level as in a non-plug-in fuel-cell hybrid 

electric vehicle, or FC-HEV). The vehicle initially operates in 

CD mode using the battery only and switches to CS mode 

after the battery reaches a low state of charge (SOC) 

threshold. In the CS phase, the fuel cell supplies the average 

power needed to propel the vehicle and maintain the SOC. 

This operating philosophy maximizes the use of inexpensive 

off-board electricity, and the driving range is limited only by 

the amount of obtainable hydrogen. However, the 

components must be large (and thus expensive) for the 

vehicle to maintain full performance capability in both CD 

and CS modes. 

Figure 1. Illustrations of the three operating 

philosophies considered for control of a FC-REV: (a) 

“traditional” SOC depletion of the battery with full 

charge sustaining capability at low SOC, (b) blended 

operation with fuel cell immediately operating at 

maximum power, and (c) two-mode strategy with initial 

all-electric operation followed by fuel cell blending. 

Figure 1b shows a blended CD operating philosophy. The 

fuel cell turns on at the start and works simultaneously with 

the battery (even when SOC is high). One advantage of this 
Wood et al / SAE Int. J. Commer. Veh. / Volume 6, Issue 2(October 2013) 

565

operating philosophy is that it enables a lower capital cost 

design because a small, continuously operating fuel cell can 

satisfy the average drive cycle energy needs with a relatively 

low-energy battery simply providing supplemental power 

(and capturing regenerative braking energy) as needed. 

However, under this philosophy the vehicle's performance 

would become restricted when either the battery fully 

depletes or the fuel cell exhausts its hydrogen supply. 

The operating philosophy in Figure 1c combines the first 

two options. The vehicle operates initially in a battery-only 

CD mode; then, once the battery has reached a predefined 

SOC trigger, a small fuel cell turns on to slow the rate of 

depletion for an extended range. This approach provides 

some balance: the operation biases toward using inexpensive 

off-board electricity when driving ranges are relatively short, 

and it only requires daily hydrogen fueling when driving 

ranges are long. The battery needs to be large enough for 

short-range independent operation, but both it and the fuel 

cell could be much smaller and less expensive than would be 

required for the “traditional” CD and CS operating 

philosophy illustrated in Figure 1a. Due to these favorable 

trade-offs, the compromise operating philosophy illustrated in 

Figure 1c was selected for the FC-REV modeling and 

simulation in FASTSim. 

ANALYSIS 

Design of Experiments 

To fully canvas the design space, a full factorial design of 

experiments was performed over a number of different 

battery, fuel cell, payload, drive cycle, operating mode, and 

SOC trigger combinations (see Table 2). The computational 

efficiency of FASTSim enabled the characterization of this 

large design space (over 63,000 simulations of 720 vehicle 

designs) in approximately 12 hours of simulation time on a 

single computer (less than one second per simulation). While 

the full experiment was simulated, the results across payload 

and drive cycle are aggregated to produce a threedimensional design space using battery energy, fuel cell 

system maximum power, and SOC trigger (the SOC trigger is 

based on usable energy and not total energy). 

The astute observer will note that hydrogen storage 

capacity was one design variable that was not swept in the 

design of experiments. This is a result of the authors' 

objective to aim for simultaneous depletion of electrical 

energy in the battery and chemical energy in the hydrogen 

storage system. To meet this objective, all simulations were 

performed with the hydrogen storage mass fixed and the 

simulated total vehicle mass varying exclusively as a function 

of battery energy and fuel cell maximum power. 

Consequently, the hydrogen storage necessary to achieve 

simultaneous battery and hydrogen depletion was calculated 

during post-processing and used to inform capital cost 

calculations for hydrogen storage. The effect of this constant 

mass assumption is believed to have minimal impact on 

simulation outcomes as the resultant hydrogen mass of the 

designs considered was on the order of tens of kilograms 

while the total vehicle simulation mass was on the order of 

thousands of kilograms. 

Table 2. Design of experiments matrix encompassing a 

number of hardware, software, duty cycle, and payload 

configurations. 

Evaluation of Vehicle Designs 

Upon completion of the design of experiments, capital 

cost, operating cost, and net present value (NPV) are 

calculated for each vehicle design. These economic outputs 

will provide the basis for design evaluation in the subsequent 

sections of this document. 

In order to calculate capital cost of each FC-REV design, 

cost models are employed for the battery, fuel cell system, 

and hydrogen storage. The battery cost model assumes a 

linear relationship between pack energy and cost with a 

coefficient of $388/kWh [3]. Fuel cell system and hydrogen 

storage costs are calculated as functions of fuel cell 

maximum power and storage capacity according to data from 

Strategic Analysis Incorporated (SA) for present day 

technology scaled up to 10,000 units/year (see Figure 2) [4]. 

As a limited number of data points for fuel cell system and 

hydrogen storage cost models were available, cost multipliers 

are held constant beyond 16 kW of fuel cell power and 4 kg 

of hydrogen storage. 

Component costs are then marked up by 50% to represent 

the price a customer or fleet vehicle purchaser could expect to 

pay [5]. Beyond the cost of the battery, fuel cell system, and 

hydrogen storage, no other vehicle costs are calculated as 

these are assumed to remain constant across all FC-REV 

designs (i.e., chassis, electric motor, power electronics, etc.). 

The ability of the proposed FC-REV designs to source 

energy from a battery and fuel cell makes the calculation of 

operating costs more involved. Following simulation, each 

vehicle design is assigned a per-mile consumption rate for 

electricity and hydrogen in both Mode 1 (prior to fuel cell 

engagement) and Mode 2 (following fuel cell engagement). 

These consumption rates are then translated to a per-mile cost 

in each mode using near-term prices for commercial 

electricity and hydrogen of $0.12/kWh [6] and $9.00/kg 

respectively (electricity price includes a markup for the 

vehicles' on-board charging efficiency, estimated at 85% [7]). 

A utility factor is then calculated for each design as the ratio 
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of miles achieved in Mode 1 to the total miles achieved in 

both modes (see Equation 1). 

Figure 2. Cost models for fuel cell system and hydrogen
	

storage. Data points sourced from SA predictions for
	

near-term technology rollout at 10,000 units per year.
	

(1) 

This ratio is calculated using the range achievable in 

Mode 1 (from simulation) and a distribution of daily vehicle 

miles traveled sourced from NREL's Fleet Testing and 

Evaluation Team [8]. Summarized graphically in Figure 3, 

this composite dataset contains mileage information from 43 

medium-duty parcel delivery vehicles collected over a total of 

737 days. All utility factor calculations in this study assume 

the vehicle is fully charged exactly once per day. 

Figure 3. Medium-duty parcel delivery drive profile data 

sourced from NREL's Fleet Testing and Evaluation 

team. 

Having derived a utility factor for each design, the permile cost from each mode is then weighted and summed 

using said utility factor to determine a singular per-mile cost 

($/mi). This per-mile cost is then multiplied by vehicle miles 

traveled (VMT) to calculate single-year fueling costs and 

projected forward assuming a vehicle lifetime of 10 years 

with future fuel purchases discounted to present day value at 

4.1% per year [9]. Annual VMT is calculated by taking 

average daily VMT and assuming operation five days/week 

(nominally 12,700 miles/year). 

Economic assumptions employed in the baseline analysis 

are summarized in Table 3. 

Table 3. Summary of assumptions used in baseline 

analysis of FC-REV, BEV, and CV powertrains. 
Wood et al / SAE Int. J. Commer. Veh. / Volume 6, Issue 2(October 2013) 

567

RESULTS 

FC-REV Optimization 

Following a complete simulation of the design space, all 

combinations of battery size, fuel cell system maximum 

power, and SOC trigger were evaluated according to the 

procedures and baseline assumptions presented in the 

previous section (please see the appendix for complete 

documentation of simulation results). The NPV of the costoptimal surface is shown in Figure 4 with battery size plotted 

on the horizontal axis and fuel cell maximum power plotted 

on the vertical axis. This two-dimensional space reflects the 

80 hardware combinations investigated. The third dimension, 

SOC trigger, was swept over nine values for each hardware 

combination to produce a total of 720 vehicle designs. For 

each hardware combination, the cost-optimal SOC trigger is 

identified and its corresponding NPV is plotted. 

Figure 4. NPV (in thousands of dollars) of cost-optimal 

designs satisfying constraints on driving range and 

hydrogen storage. Each design is represented by a square 

located at the intersection of its battery energy and fuel 

cell maximum power. 

Two constraints are placed on the design space according 

to total vehicle range and total hydrogen storage. Inspection 

of the medium-duty parcel delivery data (previously 

introduced) revealed that over 99% of vehicle days could be 

satisfied with a driving range of 150 miles. Accordingly, any 

vehicle design unable to achieve a driving range of at least 

150 miles was not considered. The second constraint placed 

on the designs was that less than 30 kg of hydrogen storage 

must be required to simultaneously deplete the battery (40-50 

kg is the nominal storage capacity of FC-HEV transit buses 

[11]). This constraint is enforced to ensure that the volume 

requirements of hydrogen storage do not infringe on the 

vehicle's primary requirement, namely to store and transport 

parcels. 

In examining the NPV of the resultant design space, it is 

worth noting that similar lifetime costs can be achieved with 

generally disparate hardware/software configurations. For 

example, four designs that round to the cost-optimal value of 

$83,000 NPV exist at significantly different points in the 

design space, as documented in Table 4. While designs A and 

B exhibit similar hardware configurations, the slightly 

smaller fuel cell in design B requires activation at a higher 

SOC to meet the 150-mile range requirement, effectively 

reducing the utility factor and offsetting the capital cost 

savings of this design. Design C takes a different approach by 

employing a battery twice as large as those in designs A and 

B. This large battery significantly increases the capital cost of 

the design, but makes up the difference by achieving a 

relatively large percentage of miles in an all-electric mode, 

reducing the frequency of high-cost hydrogen refueling. 

Finally, design D achieves a near cost-optimal NPV by 

reducing component sizes (relative to design C) and 

increasing the SOC trigger. 

Table 4. Example designs from simulation and 

evaluation of 720 hardware/software configurations. The 

four designs listed resulted in NPVs within $1,000 of one 

another. 

Ultimately, design C narrowly emerges as the costoptimal solution of this exercise. A more detailed list of 

specifications for design C is listed in Table 5. 

Table 5. Vehicle specifications for the cost-optimal 

design capable of satisfying the 150 mile minimum range 

constraint with less than 30 kg of hydrogen storage. 
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Comparison of FC-REV to BEV and CV 

While exploring the hardware/software combinations of a 

FC-REV is an interesting exercise in multi-dimensional 

design space optimization, ultimately we would like to know 

how such a powertrain compares economically with currently 

available technology. Our expectation that the energy storage 

requirements of a medium-duty BEV capable of 150 miles of 

driving range would result in a cost-prohibitive solution leads 

us to re-optimize a FC-REV design around a 60-mile 

minimum driving range constraint for purposes of 

comparison. 

In order to calculate fueling costs of a range-limited 

vehicle, our fleet parcel delivery vehicle data are appended to 

only include driving days less than 60 miles. Yearly VMT is 

then updated using the average daily distance of days less 

than 60 miles and the on-going assumption of operation five 

days/week. Updating annual VMT to consider the limitations 

of a 60-mile vehicle resulted in 9,800 miles/year of operation. 

A comparison of the optimized FC-REV design, a 60-mile 

BEV, and a CV is shown in Table 6. 

Table 6. Comparison of three powertrains with a 

minimum of 60-mile driving range capability. (Note: The 

CV calculation of a $0 capital cost neglects the baseline 

cost of the chassis and engine as a comparable cost of 

chassis and electric motor are not considered in the 

analysis of the electric powertrains.) 

In making comparisons between the FC-REV design and 

the BEV, it is worth noting that while the hardware 

specifications of the two powertrains have little in common, 

their ultimate NPVs are very similar. We see that while the 

capital cost of the BEV is significantly higher than the FCREV, the low operating costs of the BEV allow it to stay 

competitive in this space. In terms of consumer acceptance, 

an argument could be made in favor of either powertrain. The 

FC-REV affords lower capital cost, an issue that is 

consistently identified as a market barrier to advanced vehicle 

technology [12]. Alternatively, the BEV offers a potentially 

more reliable powertrain configuration (due to its relative 

simplicity) and foregoes the hydrogen infrastructure 

requirements of the FC-REV. 

In the end, the near-term argument between FC-REVs and 

BEVs is merely academic in light of the heavy economic 

advantage possessed by CVs. The NPV of a comparable CV 

is 38% less than either electric powertrain at this range; while 

the fueling costs of CVs appear relatively high, this 

difference is more than offset by the low capital cost of 

conventional technology. 

An identical economic comparison is now conducted at 

incremented driving range capabilities from 30 to 210 miles. 

The effect of a maximum single-charge driving range on 

VMT and NPV is shown in Figure 5. It can be seen that the 

BEV is only able to remain competitive with the optimized 

FC-REV design at or below 60 miles of driving range. The 

NPV of high-range BEV designs escalates quickly as the 

capital cost of the battery pack substantially increases. The 

additional range afforded by high-range BEVs simply is not 

utilized sufficiently to make them a cost-effective 

proposition. 

Figure 5. Extrapolation from parcel delivery data of how 

annual VMT changes as a function of maximum driving 

range. NPVs for a FC-REV, BEV, and CV are calculated 

for each driving range requirement and annual VMT 

combination. 

Alternatively, the FC-REV is able to achieve a high 

driving range without letting the NPV get out of control. 

Incremental capital cost increases are necessary to extend the 

driving range of a FC-REV, primarily in the form of 

increased fuel cell power and hydrogen storage. In addition to 

increases in capital cost, the FC-REV designs see fueling 

costs increase nearly proportional to VMT. 

However, it is again the CV that wins out in this nearterm lifecycle cost analysis. The CV design achieves the 

lowest NPV across all range requirements with NPV being 
Wood et al / SAE Int. J. Commer. Veh. / Volume 6, Issue 2(October 2013) 

569

directly proportional to VMT. And while markers have been 

placed for CV designs with <100 miles of range, it is not 

expected that any commercial CV would store less than 100 

miles of diesel fuel, giving the CV an even greater advantage 

in the low range capability design space. 

Given present day economic assumptions, the optimized 

FC-REV designs were unable to outpace the NPV of a CV 

under any driving range requirement. However, it is unclear 

how this comparison might change relative to a different set 

of economic conditions or under different distributions of 

daily VMT. The following section sheds light on the matter 

by exploring lifecycle costs under an array of hydrogen, 

battery, and diesel costs in addition to vehicle-specific drive 

patterns. 

Sensitivity to Economic Climate and Duty 

Cycle 

The degree to which economic conditions impact the cost 

ratio between FC-REVs and CVs is now explored. The NPV 

of a medium-duty parcel delivery vocation is calculated for 

both a CV and an optimized FC-REV for an array of 

economic inputs according to the methods outlined 

previously. For this analysis, we revert to a 150-mile range 

requirement while continuing to impose a hydrogen storage 

requirement of 30 kg or less. 

Figure 6 shows the NPVs of both powertrains as a 

function of (a) hydrogen cost, (b) battery cost, and (c) diesel 

cost. This exercise explores each variable independently (i.e., 

no combinations such as low hydrogen and low battery cost 

are explored). From these sweeps, we can see that the FCREV is able to reach cost equivalency with the CV if 

hydrogen prices reach ≈$3.50/kg or if battery costs reach < 

$100/kWh or if diesel prices reach ≈$7.00/gal. 

It should be noted that in addition to NPV, the costoptimal FC-REV design is quite sensitive to both hydrogen 

cost and battery cost. As one might expect, decreasing 

hydrogen costs lead the optimization to select small battery 

designs that are hydrogen dominant, while decreasing battery 

cost induces the opposite effect. 

Another item of interest is how the cost-optimal FC-REV 

design and its corresponding NPV might change relative to 

various distributions of daily VMT. To explore this topic, the 

cost optimal FC-REV design was identified for each of the 43 

distributions of daily VMT from NREL's sample of mediumduty parcel delivery fleet data. Here the range requirement for 

each vehicle is calculated individually as being 10% greater 

than the longest drive day. Additionally, the annual VMT of 

each vehicle in the dataset is calculated using the usual 

assumption of five operational days/week. For example, if a 

drive profile contained 40 days of data where the average 

daily distance is 30 miles and the maximum is 80 miles, only 

designs rated for 88 miles of range or greater would be 

considered and fueling costs would assume an annual VMT 

of 7,800 miles. 

Figure 6. Sensitivity of FC-REV and CV NPVs to 

changes in hydrogen, battery, and diesel costs. 

Figure 7 shows the distribution of hardware 

configurations selected as cost-optimal for each of the 43 

drive profile sets employed. Here we see total vehicle 

capability pairings as low as a 10 kWh + 6 kW and as high as 

70 kWh + 18 kW with the most popular design resting at 70 

kWh + 15 kW (X kWh of battery energy and Y kW of fuel 

cell power). It is interesting to note that the optimal design 

when considering all profiles in aggregate was a 60 kWh + 21 

kW pairing that comes in at a slightly lower capital cost. The 

high capital cost design of 70 kWh + 15 kW becomes popular 

for individual drive profiles where the longest day of 

recorded travel is very close to the average day. These 

specific profiles are able to achieve very low fueling costs by 

maximizing their utility factor with a large battery and 

purchasing as little hydrogen as possible (given the baseline 

assumption of $9/kg). 
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Figure 7. Hardware distribution for FC-REV
	

optimization performed over 43 unique distributions of
	

daily distance traveled.
	

Figure 8. Distribution of cost ratios between individually 

optimized FC-REVs and their CV counterparts. 

Lastly, the NPV of each of the individually optimized 

design is compared to the NPV of a CV over the identical 

distribution of daily VMT. In this way, a cost ratio for each 

vehicle is calculated as the NPV of the optimized FC-REV 

design divided by the NPV of the CV (i.e., a profile where 

the FC-REV NPV is less than the CV NPV would have a cost 

ratio less than one). Figure 8 shows the distribution of this 

cost ratio in addition to the cost ratio of the FC-REV 

designed for 150 miles of range and applied to the fleet data 

in aggregate. While none of the individually optimized FCREV designs are able to achieve cost equivalency with their 

CV counterparts (given the baseline assumptions), it can be 

seen that optimizing the design of the FC-REV to specific 

distributions of daily VMT can decrease NPV by up to 20%. 

SUMMARY 

This analysis has examined the potential for hydrogen 

fuel cells to be used as a range-extending power unit for 

medium-duty BEVs. Near-term economic conditions and 

real-world vocational data have been employed to make 

comparisons with battery electric and conventional vehicles. 

Market conditions necessary for FC-REVs to be competitive 

for conventional technology have been identified. 

Major conclusions from this work include: 

1. Specification of cost-optimal hardware/software 

combinations for FC-REVs is very sensitive to assumptions 

regarding economic climate and driving profile. 

2. Equivalent NPV can be achieved using disparate 

combinations of battery size and fuel cell maximum power. 

3. The FC-REV is an attractive powertrain configuration 

for achieving high single-charge driving range (>60 mi) with 

zero-emissions capability while maintaining reasonable 

capital costs. 

4. While not currently cost effective with regard to 

conventional diesel technology, FC-REVs are expected to 

become increasingly competitive as the cost of hydrogen 

production and battery manufacturing come down and 

petroleum costs increase. 

5. Accurate knowledge of a vehicle's driving profile 

offers the potential to significantly decrease lifecycle costs by 

selection of the cost-optimal FC-REV powertrain 

configuration. 

REFERENCES 

1.		 National Renewable Energy Laboratory, Transportation and Hydrogen

Systems Center, Future Automotive Systems Technology Simulator,

http://www.nrel.gov/vehiclesandfuels/vsa/fastsim.html. 

2.		 Field data from Smith Newton parcel delivery vehicle provided by

Smith Electric Vehicles via personal communication, Jan 2013.

3.		 Howell, D., “U.S. Battery R&D Progress and Plans,” U.S. Department

of Energy, Vehicle Technologies Office, Presented at the 2013 

Hydrogen and Vehicle Technologies Annual Merit Review and Peer

Evaluation Meetings, 13-17 May 2013, Arlington, Virginia.

4.		 Manufacturing cost assumptions generated by Strategic Analysis

Incorporated and provided via personal communication, Jan 2013.

5.		 Rogozhin, A., Gallaher, M., Helfand, G., and McManus, W., “Using

Indirect Cost Multipliers to Estimate the Total Cost of Adding New

Technology in The Automobile Industry,” International Journal of 

Production Economics, Apr 2010, 124 (2) 360-368, http://

www.sciencedirect.com/science/article/pii/S0925527309004344. 

6.		 U.S. Energy Information Administration, “Electricity Prices,” accessed

July 2013, http://www.eia.gov/electricity/monthly/

7.		 Douba, M., Rask, E., and Meyer, M., “Advanced Powertrain Research

Facility AVTA Nissan Leaf Testing and Analysis” Argonne National

Laboratory, Oct 2012, http://www.transportation.anl.gov/D3/data/

2012_nissan_leaf/AVTALeaftestinganalysis_Major

%20summary101212.pdf. 
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8.		 National Renewable Energy Laboratory, Transportation and Hydrogen

Systems Center, Fleet Testing and Evaluation Activity, http://

www.nrel.gov/vehiclesandfuels/fleettest/. 

9.		 The New York Time, “In Investing, It's When You Start And When You

Finish,” accessed July 2013, http://www.nytimes.com/interactive/

2011/01/02/business/20110102-metrics-graphic.html?_r=2&. 

10.		U.S. Energy Information Administration, “Gasoline and Diesel Prices,”

accessed July 2013, http://www.eia.gov/petroleum/gasdiesel/. 

11.		Eudy, L., Chandler, K., and Gikakis, C., “Fuel Cell Buses in U.S.

Transit Fleets: Current Status 2012,” NREL Technical Paper

TP-5600-56406, November 2012. http://www.nrel.gov/docs/fy13osti/

56406.pdf

12.		High-Efficiency Truck Users Forum and CalStart, “Demand Assessment

of First-Mover Hybrid and Electric Truck Fleets, 2012-2016,” Published

October 2012. 

CONTACT INFORMATION 

Transportation and Hydrogen Systems Center 

National Renewable Energy Laboratory 

15013 Denver West Pkwy MS 1634 

Golden, CO 80401 

Eric Wood 

(303) 275-3290 

eric.wood@nrel.gov 

Lijuan (Joann) Wang 

(303) 275-4436 

lijuan.wang@nrel.gov 

Jeffrey Gonder 

(303) 275-4462 

jeff.gonder@nrel.gov 

Michael Ulsh 

(303) 275-3842 

michael.ulsh@nrel.gov 

ACKNOWLEDGMENTS 

This study was supported by the Fuel Cell Technologies 

Office under contract number DE-AC36-08-GO28308 by 

way of the U.S. Department of Energy's Office of Energy 

Efficiency and Renewable Energy. The authors would 

specifically like to thank Pete Devlin of the U.S. Department 

of Energy for his guidance and support. Use of the FASTSim 

vehicle modeling tool, developed at the National Renewable 

Energy Laboratory under funding from the U.S. Department 

of Energy's Vehicle Technologies Office, was critical to the 

completion of this study. Special thanks to Aaron Brooker for 

supporting our use of FASTSim. 

DEFINITIONS/ABBREVIATIONS 

BEV - battery electric vehicle 

CD - charge depleting 

CS - charge sustaining 

CV - conventional vehicle 

FASTSim - Future Automotive Systems Technology 

Simulator 

FC-HEV - fuel cell hybrid electric vehicle 

FC-REV - fuel cell range extended vehicle 

H2 - hydrogen 

HD UDDS - Heavy Duty Urban Dynamometer Driving 

Schedule 

HEV - hybrid electric vehicle 

NPV - net present value 

NREL - National Renewable Energy Laboratory 

NYCC - New York City Cycle 

OC Bus - Orange County Bus 

SA - Strategic Analysis Incorporated 

SOC - state of charge 

VMT - vehicle miles traveled 
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APPENDIX 

Figure A1. Simulation results of 80 hardware configurations in Mode 1 (prior to fuel cell engagement). Electrical consumption
	

from the battery is shown at left and hydrogen consumption from the fuel cell shown at right. A small amount of hydrogen was
	

consumed in Mode 1 on cycles where high power demands coupled with high payloads required intermittent fuel cell operation.
	

Figure A2. Simulation results of 80 hardware configurations in Mode 2 (following fuel cell engagement). Electrical
	

consumption from the battery is shown at left and hydrogen consumption from the fuel cell shown at right.
	
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Figure A3. Hydrogen storage required to achieve simultaneous battery and hydrogen depletion shown at left; resultant total
	

driving range shown at right.
	

Figure A4. Capital cost of hardware combination (battery, fuel cell system, and hydrogen storage only) shown at left; combined
	

Mode 1 and Mode 2 energy cost per mile shown at right.
	
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Figure A5. Achieved utility factor when applied to fleet medium-duty parcel delivery data shown at left; optimal SOC trigger
	

point for each hardware combination shown at right.