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5 Contents Executive Summary... 1 Introduction... 2 Objective... 2 Approach... 2 Sizing of Fuel Cell Electric Vehicles... 3 Assumptions... 5 Sizing Results... 7 Results: Midsize FC HEV and FC PHEV... 8 Contribution of Fuel Cell Technology Progress Results: Impact of Fuel Cell Technologies Conclusions References Appendix Figures Figure 1. Process for running and analyzing large-scale simulations... 3 Figure 2. FC HEV powertrain sizing algorithm... 4 Figure 3. FC PHEV powertrain sizing algorithm... 5 Figure 4. Specific power and power density for fuel cell systems... 5 Figure 5. Fuel cell system efficiency... 6 Figure 6. Fuel cell system and electric-machine power for midsize FC HEVs... 7 Figure 7. Fuel cell system power and usable battery energy for midsize FC PHEVs... 7 Figure 8. Battery energy as a function of vehicle mass for midsize FC PHEVs... 8 Figure 9. Gasoline equivalent fuel consumption for midsize FC HEVs... 8 Figure 10. Gasoline equivalent fuel consumption and electrical consumption for midsize FC PHEVs (all values are CD+CS)... 9 Figure 11. Gasoline equivalent fuel consumption for midsize power-split HEVs compared with sameyear, same-case midsize FC HEVs Figure 12. Gasoline equivalent fuel consumption for midsize FC HEVs compared with same-year, same-case midsize gasoline HEVs (left) and reference case midsize gasoline HEVs (right) Figure 13. Manufacturing costs of midsize fuel cell vehicles Figure 14. Manufacturing costs of midsize FC HEVs compared with same-year conventional gasoline vehicles iii

6 Figure 15. Incremental manufacturing costs of fuel cell vehicles (left) and all powertrains (right) compared with manufacturing costs of reference conventional gasoline vehicle as a function of fuel consumption Figure 16. Autonomie model of an FCEV Figure 17. Impact of fuel cell and hydrogen technologies on FCEV mass Figure 18. Variation in fuel cell power requirement with respect to the changes expected in fuel cell and hydrogen systems Figure 19. Reduction in onboard hydrogen requirement Figure 20. Assumptions on fuel cell system efficiency and cost Figure 21. Variation in cost of fuel cell stack from technology progress Figure 22. Impact of technology on hydrogen storage costs Figure 23. Impact of fuel cell and hydrogen technologies on FCEV cost Figure 24. Impact of fuel cell and hydrogen technologies on lifecycle cost of FCEVs Figure 25. Impact of technology progress on the cost of driving an FCEV Tables Table 1. Fuel cell system assumptions... 6 Table 2. Hydrogen storage assumptions... 6 iv

7 Executive Summary This study evaluates the fuel consumption and cost of ownership for fuel cell electric vehicles (FCEVs). Many technologies applicable to vehicles are expected to improve over the next three decades. These changes could alter the vehicle characteristics and in turn affect their fuel consumption and cost. The assumptions on the progress of various technologies is based on a DOE baseline and scenario analysis (BaSce) (Moawad et al. 2016), which compiles such information from various sources including national laboratories, government agencies, and advisory groups from automotive industry. This report is a closer look at the effects of fuel cell efficiency and hydrogen tank weight. Vehicle weight is the primary concern for FCEVs. Present technology aims at storing hydrogen at high pressure in onboard storage tanks. Such tanks are heavy since they must withstand high pressure and survive minor accidents typical in automobile usage. As a result, a tank that stores about five kilograms of hydrogen could weigh over 100 kilograms (kg). The efficiency of fuel cells is already higher than many prime movers used in the automotive industry. Further efficiency improvements could reduce the amount of hydrogen that must be stored onboard, which in turn will reduce storage system weight. Improvements in efficiency and reductions in weight are usually achieved by using relatively expensive materials, which increase vehicle cost. Several factors are involved in determining if and when a technology can gain acceptance in the automotive sector. Initial costs, operating costs, environmental aspects, and convenience all play significant roles. In this analysis, we focus on the cost of the technology. By combining initial and operating costs into a metric named levelized cost of ownership, the real cost of a vehicle can be compared. This methodology is explained later in the report. DOE has developed technology targets as benchmarks for technology development. These targets are a combination of parameters, such as efficiency, weight, volume, and cost. While the industry might be able to meet some aspects of these goals by itself, DOE research and development effort is needed to achieve all the goals. Many of the vehicle technologies have synergies that help achieve the vehicle level goals. For example, light-weighting of the chassis helps reduce losses in all kinds of vehicles. This study focuses on the following two questions: (1) What levels of technology are needed for fuel cells to be economically viable on their own merit, and (2) If improvements in other vehicle technologies are also considered, can FCEVs become economically viable at lower technology levels? Technology levels are expected to improve over the years, as explained in the body of this paper. This study shows that by year 2030, if fuel cell technologies progress as expected, the cost of owning and driving an FCEV will decrease by 17% to 43 cents per mile, and will be comparable to present day conventional vehicles. If other technologies achieve a high level of progress, the economic feasibility of FCEVs could accelerate. This report demonstrates that if the technology targets set by DOE are achieved, FCEVs will be a clean, affordable, and economically feasible choice within the next 15 years. 1

8 Introduction The U.S. Department of Energy (DOE) is committed to developing technologies that will meet the transportation energy requirements, while lowering costs, reducing petroleum dependency, and minimizing environmental effects. Advanced powertrain options, such as hybrids and plug-in hybrids, are expected to be temporary solutions that will eventually give way to battery electric vehicles and fuel cell powered vehicles. DOE s Fuel Cell Technology Office (FCTO) supports research work needed to develop technologies that enable a full range of affordable FCEVs. To establish the fuel cell component requirements on a wide range of vehicles, and to examine the economic feasibility of FCEVs when compared to other advanced vehicle choices, FCTO directed Argonne to conduct a techno-economic analysis on fuel cell and hydrogen storage systems. This report summarizes the work done on this topic over fiscal years 2015 and Some of these simulations were performed as a part of the DOE baseline and scenario analysis (BaSce) process (Moawad et al. 2016). Although the BaSce defined assumptions, sized components, and performed simulations and analyses for several kinds of vehicles, this report explains the methodologies and results using a midsize fuel cell powered vehicle as an example. Objective The objective of the study is to quantify the energy consumption and cost of fuel cell hybrid electric vehicles (FC HEVs) for all vehicles in different timeframes (2015, 2020, 2025, 2030, and 2045). Uncertainties were included for both performance and cost aspects by considering three cases (uncertainty at 10%, 50%, and 90%). These uncertainties represent the evolution of technology aligned with original equipment manufacturer improvements based on regulations (10%), as well as an aggressive advancement of technology advancement based on the DOE Vehicle Technologies Program (VTP) (90%). Approach To assess the benefits of future technologies properly, the study considered different timeframes representing different sets of assumptions. However, this paper focuses on a single vehicle class (midsize). For this study, we will use laboratory years 2015, 2020, and It should be noted that laboratory year 2015 reflects a vehicle available in the market in 2020 (current technology). Similarly, laboratory, or simulation, year 2025 reflects a vehicle in the market in 2030, and simulation year 2030 reflects a vehicle in the market in Additionally, to address uncertainties this report employed a triangular distribution approach (low, medium, and high). The study made assumptions for each component (e.g., efficiency, power density) and defined three separate values to represent the ninetieth percentiles, fiftieth percentiles, and tenth percentiles. A 90% probability means that the technology has a 90% chance of being available at the time considered. For each vehicle case (particular class, technology uncertainty, simulation year), simulations were performed with the evolution of all vehicle technologies simultaneously. The bar charts herein represent this uncertainty with an error bar. All simulations discussed in this paper were performed with Autonomie, a modelling tool developed by Argonne National Laboratory (Argonne 2017). Autonomie is a plug-and-play model development environment that supports the rapid evaluation of new powertrain technologies. The model and control library provided by Autonomie is forward-looking and is written in Matlab, Simulink, and Stateflow. To evaluate the benefit of advanced fuel cells and hydrogen tank systems on fuel efficiency, each vehicle design uses individual components assumed to meet the same vehicle technical specifications (VTS) (acceleration, grade-ability, etc.). The vehicle s fuel efficiency is then simulated with the Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Test (HWFET). The vehicle costs are calculated using the aggregated cost of each component. Figure 1 illustrates the process, which comprises two distinct phases. The objective of the first phase is to set up the simulations, launch all the runs through a distributed computing toolbox, and analyze the individual results to ensure the simulations are performed properly. 2

9 Figure 1. Process for running and analyzing large-scale simulations The objective of the second phase is to allow users to analyze a limited number of parameters from the individual simulations and perform large-scale analysis. As shown in Figure 1, this process starts by developing a standardized query language database founded on a list of user-defined parameters. The objective of the database analysis tool allows users to, for example, select the most cost-beneficial technologies and understand uncertainties. Sizing of Fuel Cell Electric Vehicles To compare different vehicle technology combinations, all study vehicles were sized to meet the same requirements: Acceleration from initial vehicle movement to 60 miles per hour (mph): less than 9 seconds ±0.1 second Acceleration from 50 mph to 80 mph: less than 9 seconds ±0.1 second Maximum grade: 6% at 65 mph at gross vehicle weight Maximum vehicle speed: greater than 100 mph Improperly sized components would lead to differences in energy consumption, influencing the results. On this basis, we developed automated sizing algorithms to provide a fair comparison between technologies. The algorithms are based on the following concept: the vehicle is built from the bottom up, meaning each component assumption (e.g., specific power, efficiency) is taken into account to define the entire set of vehicle attributes (e.g., weight). This process is always iterative in the sense that the main component characteristics (e.g., maximum power, vehicle weight) are changed until all VTSs are met. On average, the algorithm takes between 5and 10 iterations to converge. Figure 2 shows the iterative process for the FC HEV powertrain. 3

10 Figure 2. FC HEV powertrain sizing algorithm The main assumptions for the sizing algorithm for FC HEV are: Fuel cell power: Sized to meet 70% of peak power required for VTS (acceleration performance or gradeability); fuel cell peak power is a function of the vehicle weight. Battery power: Sized to recuperate 100% energy on UDDS; battery cell number is a function of the vehicle weight. Electric machine (EM) power: Sized to follow the US06 in EV mode at low State-of-Charge (SOC) or to meet the requirement of acceleration performance. Vehicle weight: Vehicle weight is a function of the fuel cell peak power, EM peak power, and number of battery cells. The main algorithms for the fuel cell plug-in hybrid electric vehicle (FC PHEV) powertrain are: Fuel cell power: Sized to meet 70% of peak power required for VTS (acceleration performance or gradeability); fuel cell peak power is a function of the vehicle weight. Battery energy: Sized to meet the all electric range (AER) requirements on UDDS, based on unadjusted values. Using the full history of the range attained by the vehicle from each sizing run, the desired range, and the current battery energy, the algorithm makes a new estimate for the desired battery energy. EM power: Sized to follow the UDDS cycle (low energy PHEV; blended), or US06 cycle (high energy PHEV; extended range) in electric-only mode (this control is only used for the sizing), or to meet the acceleration performance requirements. Vehicle weight: Vehicle weight is a function of the engine peak power, EM peak power, and battery energy. The iterative process is shown in Figure 3. 4

11 Figure 3. FC PHEV powertrain sizing algorithm Assumptions The assumptions for each component were developed in collaboration with experts from DOE, national laboratories, industry, and academia. When available, the high case assumptions were based on program goals. The following sections provide information for a very limited set of assumptions relating to the FCEVs. Figure 4 shows the specific power and specific energy of the fuel cell system. Between the reference case and year 2045, the specific power increases from 659 W/kg to 870 W/kg, or an increase ranging from 1.5 % to 32% (Table 3). The fuel cell system model used for the study was based on a steady-state look-up table. The fuel cell system map (5x mass activity) was provided by the Argonne Fuel Cell Group using the General Computational Toolkit. Figure 4. Specific power and power density for fuel cell systems 5

12 Table 1. Fuel cell system assumptions Parameter Units Ref FC System- Specific Power low med high low med high low med high low med high low med high W/kg Power Density W/L Peak FC Efficiency at 25% Rated Power Platinum Price % $/troy oz As a result, the additional losses from the balance of plant due to transient operating conditions were not taken into account. The fuel cell system simulated has been sized to range 320 miles on the adjusted combined cycle. The fuel cell system costs are driven by the following equation: (1,246.5 x S P y) FC pwr. ( FC pwr 80 )z, (1) where x, y, and z are coefficients; P is the platinum price; S is the stack unit per year; and FC pwr is the fuel cell power. The cost is based on high production volumes (500,000 per year). Figure 5 shows the evolution of the fuel cell system peak efficiencies. The study assumes a peak fuel cell efficiency of 59 % for the reference year and an increase up to 70% by Table 2. Hydrogen storage assumptions Parameter Units Ref System Capacity Tank Cost H 2 Used in Tank Useable kwh/kg Useable kg H 2/kg of tank $/Useable kg H 2 Figure 5. Fuel cell system efficiency low med high low med high low med high low med high low med high % Range* miles * Based on combined, adjusted mpg gasoline equivalent. 6

13 The hydrogen storage cost and hydrogen mass are calculated as follows: and H 2cost = C H2 M fuel (2) H 2mass = M fuel Cap H2, where C H2 is the hydrogen cost coefficient ($/kg H 2), Cap H2 is the hydrogen gravimetric capacity (kg H 2/kg tank), and M fuel is the hydrogen fuel mass (kg). Sizing Results Fuel cell systems show a decrease in peak power over time, owing primarily to vehicle light-weighting and fuel efficiency improvements. The total decrease from the reference case to the 2045 case ranged from 20% to 41%. Figure 6 shows that the EM peak power decrease ranges from 15% to 34% between 2010 and (3) Figure 6. Fuel cell system and electric-machine power for midsize FC HEVs The fuel cell system power decreases over time for all the AERs, with reductions ranging from 22% to 46% (Figure 7). From one AER to another, the changes in fuel cell power are very small. The usable battery energy for fuel cell PHEVs follow the same pattern described for power-split PHEVs, as can be observed in Figure 7. The energy is proportional to the AER, and it decreases continuously over time. For all of the AERs, the usable battery energy is from 20%to 41% lower (PHEV10) 22% to 43% lower (PHEV20); 29% to 48% lower (PHEV30); and 30% to 51% lower (PHEV40) by 2045, compared with the reference case. The rate of change appears to increase with higher AER. Figure 7. Fuel cell system power and usable battery energy for midsize FC PHEVs 7

14 Figure 8 shows that the battery energy is proportional to the AER for the various PHEVs. If the AER doubles, the battery energy will also double. The PHEVs all show a linear relationship between the battery energy and the vehicle mass, however it appears the higher the AER, the greater the slope. Results: Midsize FC HEV and FC PHEV Figure 8. Battery energy as a function of vehicle mass for midsize FC PHEVs The fuel consumption results shown in this report are expressed in liters per 100 km. All the fuel consumption results are provided for the combined drive cycle using unadjusted values based on gasoline equivalent. Figure 9 shows that fuel consumption decreases over time. The FC HEVs consume from 35% to 56% less fuel by 2045 compared with the reference case (2010). Figure 9. Gasoline equivalent fuel consumption for midsize FC HEVs For fuel cell PHEVs, the fuel consumption decreases slowly (Figure 10) as the AER goes from one range to the next higher range. The reasons for the decrease are the same as discussed for power-split PHEVs. From 2010 to 2045, the consumption decreases by 35% to 57% for all the AERs. Note that this rate of change coincides with the decrease of FC HEV fuel consumption. Figure 10 shows that electrical consumption also decreases considerably from 2010 to Initial consumption levels increase within the AER for any given year. 8

15 Figure 10. Gasoline equivalent fuel consumption and electrical consumption for midsize FC PHEVs (all values are CD+CS) The fuel consumption ratios for all types of power-split HEVs versus FC HEVs (Figure 11) are higher than one, showing that fuel cell technology offers consistently lower fuel consumption than power-split HEV technology. However, the ratios vary over time, and it is pertinent to study the evolution for each fuel. In the reference case, this vehicle consumes nearly 48% more fuel than an FC HEV; in 2045, however, this difference drops to 29% (gasoline HEV). Figure 11. Gasoline equivalent fuel consumption for midsize power-split HEVs compared with same-year, same-case midsize FC HEVs. Figure 12 (left) shows that, in the reference case, the FC HEVs consume about 56% less fuel than conventional gasoline vehicles. In 2015, this difference in fuel consumption decreases to 54% because of the rapid evolution of engine technologies. By 2015, engine peak efficiency increases from 38% to 41%; however, the fuel cell peak efficiency remains unchanged at 59%. In 2045, the difference in fuel consumption increases range from 60% to 63%, indicating that, by 2045, the fuel consumption of the gasoline HEV will not improve as fast as the fuel consumption of the FC HEV. In contrast, Figure 12 (right) shows that, in the reference case, FC HEVs consume about 56% less fuel than gasoline HEVs. This difference in fuel consumption increases in the 2045 timeframe to reach ratios of 0.3 to 0.2, or a difference of 70% to 80%. 9

16 Figure 12. Gasoline equivalent fuel consumption for midsize FC HEVs compared with same-year, samecase midsize gasoline HEVs (left) and reference case midsize gasoline HEVs (right) Fuel cell vehicle manufacturing costs (Figure 13) show a pattern similar to previously described gasoline vehicle manufacturing costs. Indeed, as time goes on, the manufacturing costs of the different vehicles become closer to each other. In 2010, an FC PHEV40 is approximately 40% more expensive than an FC HEV, whereas in 2045, the costs are almost equal. Finally, it is interesting to note that in 2045, the fuel cell vehicle manufacturing costs are under $20,000 for all the average and high cases. Figure 13. Manufacturing costs of midsize fuel cell vehicles Figure 14 shows the manufacturing cost ratio between fuel cell and same-year conventional gasoline vehicles. The FC HEV is about 80% more expensive than the conventional gasoline vehicle. This difference, however, tends to decrease after From 2015 on, the cost ratio of the vehicle decreases, reaching almost 1.1 in This observation can be explained by improvements in fuel cell system and hydrogen storage over time. 10

17 Figure 14. Manufacturing costs of midsize FC HEVs compared with same-year conventional gasoline vehicles Figure 15 (left) shows the trade-offs between incremental manufacturing cost and fuel consumption for fuel cell HEVs and PHEVs compared with the reference conventional gasoline vehicles. For the PHEVs, we found a diminishing return on investment, since little fuel efficiency gain is achieved for the higher AER despite a higher manufacturing cost. Overall, all configurations trend toward good fuel efficiency at a low manufacturing cost. Figure 15 (right) shows the trade-offs between fuel consumption and increased manufacturing costs for all powertrains and fuels compared with the conventional gasoline reference case. Overall, the vehicles on the bottom right would provide the best fuel consumption for the least additional cost. All years, all cases, and all fuels are presented. Figure 15. Incremental manufacturing costs of fuel cell vehicles (left) and all powertrains (right) compared with manufacturing costs of reference conventional gasoline vehicle as a function of fuel consumption Contribution of Fuel Cell Technology Progress While the BaSce analysis (Moawad 2016) demonstrated the feasibility of FCEVs when combined with varying levels of progress in other vehicle technologies, the scenario in this report eliminates the uncertainties related to the progress of other technologies. Here, we assume the worst-case scenario, where all technologies except fuel cells stagnate at their current level. Therefore, the baseline vehicle chosen for this analysis is the laboratory year 2015 FC HEV used in the BaSce analysis. The range of the FC HEV is set at 320 miles and has the same performance as conventional vehicles currently in the market. Autonomie enables us to evaluate the fuel economy and initial and operating costs for such a vehicle. See Figure 16 for a graphic of the Autonomie model of an FCEV. This study does not consider the PHEV version, as the focus of the study is on fuel cell systems. 11

18 Figure 16. Autonomie model of an FCEV The FC HEV is considered a feasible choice when it achieves the same or lower lifecycle cost (cost per mile) as a conventional vehicle. For each target year, the expected improvements in FCEV-specific technologies are added to this baseline vehicle model. Simulation results provide the improvement observed in vehicle mass, power, onboard hydrogen storage, and cost. Three scenarios are evaluated for each year: 1. Fuel cell system impact: Fuel cell system improves over time at high technology progress rates, 2. Hydrogen storage system impact: Hydrogen storage system improves over time, and 3. Combined hydrogen storage-fuel cell impact: Both fuel cell and hydrogen systems improve over time. This evaluation reveals the relative importance of each FCEV-specific technology, as well as their combined contribution in making FCEVs technically and economically viable. Results: Impact of Fuel Cell Technologies Improvements in general vehicle technologies, like aerodynamic improvements or glider light-weighting, are not considered for this study. The focus here is on various technologies funded by FCTO and their impact on the vehicle. Vehicle mass Vehicle mass is the primary factor that varies with any improvement in the storage technology or fuel cell system. Improving the hydrogen tank pressure or increasing the usable fraction of hydrogen in a tank result directly in reducing the weight of the tank. Even improving the fuel cell efficiency reduces the requirement of onboard hydrogen, which in turn results in a smaller tank and lower vehicle weight. Increased power and energy density for the fuel cell stack and reduced weight of hydrogen storage systems result in lower vehicle mass, as shown in Figure 17. The left-most plot shows improvements in mass attributable to changes in fuel cell stack efficiency and power density. The second plot shows the difference in vehicle mass arising from improvements in hydrogen storage technologies. The right-most plot shows the combined improvement from these technologies could result in reducing the vehicle mass by approximately 100 kg. Based on the low or high technology progress case, an error bar is associated with these predictions, and also for the vehicle mass predictions. 12

19 Fuel cell power Figure 17. Impact of fuel cell and hydrogen technologies on FCEV mass A lighter vehicle requires less power from the prime mover and less energy storage onboard. To account for these cumulative effects, the vehicle is subjected to a sizing process whenever a change is made. Improving the fuel cell efficiency and reducing the hydrogen tank weight has secondary effects on the vehicle weight, resulting in slightly lower power requirements from the fuel cell stack. However, the effect of these changes on the fuel cell power requirement is limited to a few kilowatts as shown in Figure 18. Figure 18. Variation in fuel cell power requirement with respect to the changes expected in fuel cell and hydrogen systems Onboard hydrogen requirement The FCEVs should have the same effective range as their conventional counterparts they must have enough onboard hydrogen storage to run approximately 320 miles. The hydrogen mass requirement is decided by the overall fuel economy of the vehicle. The fuel cell stack improvements play a significant role in determining how much fuel has to be carried onboard. As fuel stacks improve, the vehicle could see a 10% to 18% reduction in the hydrogen required onboard. Figure 19 shows variations in the mass of hydrogen required for the vehicle with different technology improvements. 13

20 Fuel cell system cost Figure 19. Reduction in onboard hydrogen requirement As fuel cell technology improves, the efficiency will improve by about 20% and the cost will decline to approximately half of the current value. These assumptions are shown in Figure 20. Figure 20. Assumptions on fuel cell system efficiency and cost At present, fuel cell cost is close to 20% of the FCEV cost. Based on our assumptions, fuel cell cost is expected to come down in the future, as shown in Figure 21, and this reduction will help reduce the overall vehicle cost, as well. 14

21 Figure 21. Variation in cost of fuel cell stack from technology progress It is interesting to note that improvements in the hydrogen storage system can indirectly result in lower fuel cell stack cost. Over 13% improvement is expected in the overall gravimetric capacity of the hydrogen storage system in the next five years. This change brings about a significant reduction in the overall power requirement of the fuel cell stack, resulting in reduced cost. Hydrogen storage cost The increased fraction of usable hydrogen per kilogram of tank helps to reduce tank size and cost. Improved efficiency of the fuel cell stack also results in a lower hydrogen requirement and helps reduce the storage cost. The improvements in hydrogen storage cost from various technologies are shown in Figure 22. FC HEV cost Figure 22. Impact of technology on hydrogen storage costs The cumulative effect of the reduction in hydrogen storage and fuel cell stack costs can be seen in the overall vehicle cost. Simulations predict about a 20% improvement in FCEV fuel economy by The better fuel economy will result in reduced component cost, as well as operational costs. Figure 23 shows the overall reduction in vehicle cost expected in the next three decades. 15

22 Figure 23. Impact of fuel cell and hydrogen technologies on FCEV cost Figure 24 shows the overall lifecycle cost reduction that could be expected, which reflects the lower recurring costs resulting from the higher fuel economy of the future vehicles. Figure 24. Impact of fuel cell and hydrogen technologies on lifecycle cost of FCEVs Present day conventional vehicles have a lifecycle cost of 43 cents per mile, which would increase slightly in the future owing to stricter environmental regulations. Even if the increase in conventional vehicle ownership cost is not factored in, FCEVs are expected to have a similar ownership cost by 2030, if the fuel cell technology targets are met. If all vehicle technologies develop as expected, then the combined improvements in batteries, motors, and vehicle light weighting, by themselves, could make fuel cells competitive by

23 Figure 25. Impact of technology progress on the cost of driving an FCEV Conclusions This study shows that if the 2030 technology targets for fuel cell technologies are achieved, then FCEVs can be economically feasible, even with present day vehicle technologies. The current technology targets for 2030 are sufficient to overcome any uncertainties associated with other vehicle technologies. If fuel cell technologies progress as assumed, by 2030 the cost of owning and driving an FCEV will drop by 17% to 43 cents per mile and will be comparable to present day conventional vehicles. If other technologies also achieve a high level of progress, by 2025 fuel cell powered vehicles will become an economically feasible alternative to conventional gasoline powered vehicles. Fuel cell efficiency improvements play an important role in making FCEVs viable. Better efficiency could reduce the overall onboard fuel storage requirement, and in turn reduce the mass of the tank required for the vehicle. Manufacturing costs will decrease primarily from both fuel cell system and hydrogen tank cost decreases. References Argonne (Argonne National Laboratory) Autonomie (software). Moawad, A., N. Kim, N. Shidore, and A. Rousseau Assessment of Vehicle Sizing, Energy Consumption and Cost through Large Scale Simulation of Advanced Vehicle Technologies, report ANL/ESD- 15/28. Argonne, IL: Argonne National Laboratory. 17

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