Evolution of Hydrogen Fueled Vehicles Compared to Conventional Vehicles from 2010 to 2045

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1 29--8 Evolution of Hydrogen Fueled Vehicles Compared to Conventional Vehicles from 2 to Antoine Delorme, Aymeric Rousseau, Phil Sharer, Sylvain Pagerit, Thomas Wallner Argonne National Laboratory Copyright 27 SAE International ABSTRACT Fuel cell vehicles are undergoing extensive research and development because of their potential for high efficiency and low emissions. Because fuel cell vehicles remain expensive and there is limited demand for hydrogen at present, very few fueling stations are being built. To try to accelerate the development of a hydrogen economy, some original equipment manufacturers in the automotive industry have been working on a hydrogenfueled internal combustion engine (ICE) as an intermediate step. This paper compares the fuel economy potential of hydrogen powertrains to conventional gasoline vehicles. Several timeframes are considered: 2, 25,, and. To address the technology status uncertainty, a triangular distribution approach was implemented for each component technology. The fuel consumption and cost of five powertrain configurations will be discussed and compared with the conventional counterpart. INTRODUCTION The 993 Government Performance and Results Act (GPRA) holds federal agencies accountable for using resources wisely and achieving program results. The GPRA requires agencies to develop plans for what they intend to accomplish, measure how well they are doing, make appropriate decisions on the basis of the information they have gathered, and communicate information about their performance to Congress and to the public. Every year, a report is published [] to assess the results and benefits of the different programs. The current study evaluates the benefits of the light-duty vehicle research conducted at the U.S. Department of Energy from fuel efficiency and cost perspectives. The different technologies were simulated by using the Powertrain System Analysis Toolkit (PSAT). Argonne designed PSAT [2, 3] to serve as a single tool that can be used to meet the requirements of automotive engineering throughout the development process, from system modeling to control. Because of time and cost constraints, designers cannot build and test each of the many possible powertrain configurations for advanced vehicles. PSAT, a forward-looking model developed with Matlab, Simulink, and StateFlow, offers the ability to quickly compare several powertrain configurations from a performance and fuel efficiency point of view. Component costs were gathered from experts to later evaluate market penetrations. The current study evaluates the potential fuel efficiency and cost of hydrogen fueled vehicles compared to gasoline vehicles for several time frames. METHODOLOGY Advanced vehicles are designed on the basis of various component assumptions. The fuel efficiency is then determined by a simulation on the Urban Dynamometer Driving Schedule (UDDS) and Highway Federal Emissions Test (HWFET). The vehicle costs are calculated from the component sizing. Both cost and fuel efficiency are then used to define the market penetration of each design to finally estimate the amount of fuel saved. The process is summarized in Figure. This paper will focus on the first phase of the project: assessment of fuel efficiency and cost. Assumptions Figure : Process to Evaluate Vehicle Fuel Efficiency of Advanced Technologies To properly assess the benefits of future technologies, we considered several options, as shown in Figure 2: Vehicle Simulation Fuel Electricity Cost Market Penetration Fuel Saved Four vehicle classes: midsize car, small SUV, medium SUV, and pickup truck

2 Five timeframes: current, 2, 25,, and Five powertrain configurations: conventional, hybrid electric vehicle (HEV), plug-in HEV (PHEV), fuel cell HEV, and electric vehicle Four fuels: gasoline, diesel, ethanol, and hydrogen Overall, more than 7 vehicles were defined and simulated in PSAT. The current study does not include micro or mild hybrids and does not focus on emissions. Figure 2: Vehicle Classes, Timeframes, Configurations, and Fuels Considered To address uncertainties, we employed a triangular distribution approach (low, medium, and high), as shown in Figure 3. For each component, assumptions were made (efficiency, power density, etc.), and three separate values were derived to represent () the 9 th percentile, (2) 5 th percentile, and (3) th percentile. A 9% probability means that the technology has a 9% chance of being available at the time considered. For each vehicle considered, the cost assumptions also follow the triangular uncertainty approach. Each set of assumptions is, however, used for each vehicle, and the most efficient components are not automatically the cheapest ones. As a result, for each vehicle considered, we simulated three options for fuel efficiency. Each of these three options also has three values representing the cost uncertainties. Glider Mass Reduction (%) Vehicle Classes 5 Glider Mass Reduction 2 25 Timeframes Current 2 25 Drag Coefficient Powertrain Configurations Conventional PHEV Electric Drag Coefficient - Car 2 25 ICE HEV Fuel Cell Triangular analysis was used for each assumption Cost ($/kw) Gasoline Fuels Ethanol Diesel Fuel Cell System Cost 2 25 The following section describes the assumptions and their associated uncertainties for each component technology. COMPONENT TECHNOLOGY ASSUMPTIONS ENGINES - Several state-of-the-art engines were selected for the fuels considered: gasoline, diesel, E85 FlexFuel, and hydrogen. The data on gasoline, diesel, and E85 FlexFuel engines for current conventional vehicles were provided by automotive car manufacturers, while data for port-injected hydrogen engines were generated at Argonne [4]. The engines used for HEVs and PHEVs are based on Atkinson cycles, generated from test data collected at Argonne s dynamometer testing facility [5]. Different options were considered to estimate the evolution of each engine technology. Although linear scaling was used for gasoline and E85 (HEV application only) and diesel engines, direct injection with linear scaling was considered for the hydrogen-fueled engine [5], and nonlinear scaling based on Bandel s work [6] was used for gasoline and E85 (conventional applications). For the non-linear scaling, different operating areas were improved by different amounts, which resulted in changing the constant efficiency contours. The peak efficiencies of the different fuels are shown in Figure 4. Figure 4: Engine Efficiency Evolution FUEL CELL SYSTEMS - The fuel cell system model is based on the steady-state efficiency map shown in Figure 5. The fuel is assumed to be gaseous hydrogen. In simulation, the additional losses due to transient operating conditions are not taken into account. Low Med High Uncertainty Low Med High Uncertainty Low Med High Uncertainty 9% vehicle 5% vehicle % vehicle Figure 3: Triangular Uncertainty Approach

3 Figure 5: Fuel Cell System Efficiency versus Fuel Cell System Power from the System Map Figure 6 shows the peak efficiencies of the fuel cell system and its corresponding cost. The peak fuel cell efficiency is assumed to be currently at 55% and to increase to 6% by 25. The value of 6% has already been demonstrated in laboratories and, therefore, is expected to be implemented soon in vehicles. The peak efficiencies remain constant in the future, as most research is expected to focus on reducing cost. The costs are projected to decrease from $8/kW currently (values based on high production volume) to an average of $45/kW in (uncertainty from $3 to $6/kW). Figure 7: Hydrogen Storage Capacity in Terms of Hydrogen Quantity One of the requirements for any vehicle in the study is that it must be able to travel 32 miles on the Combined Driving Cycle with a full fuel tank. However, if we wanted to simulate current vehicles with a hydrogen storage system allowing a driving range of 32 miles, the amount of hydrogen needed, and thus the corresponding fuel tank mass, would be too large to fit in the vehicles. As a result, different ranges were selected: Reference, 2, and 25: 9 miles and : 32 miles ELECTRIC MACHINES - Figure 8 shows the electric machine peak efficiencies considered. The values for the current technologies are based on state-of-the-art electric machines currently used in vehicles [7]. The electric machine data from the Toyota Prius and Toyota Camry were used for the power-split HEV application, while the electric machine used in the Ballard Integrated Powertrain (IPT) was selected for series fuel cell HEVs. Because the electric machine is already extremely efficient, most of the improvements reside in cost reduction, as shown in Figure 9. Figure 6: Fuel Cell System Efficiency and Cost HYDROGEN STORAGE SYSTEMS - The evolution of hydrogen storage systems is vital to the introduction of hydrogen-powered vehicles. Figure 7 shows the calculated evolution of hydrogen storage capacity. Figure 8: Electric Machine Peak Efficiency

4 Figure 9: Electric Machine Cost ENERGY STORAGE SYSTEM - Energy storage systems are a key component in advanced vehicles. Although numerous studies are being undertaken with ultracapacitors, only batteries were taken into account in this study. All current vehicles are defined as using nickel/metal hydride (NiMH) battery technology. The Liion technology is introduced for the high case in 2 and for the medium and high cases in 25 before becoming the only one considered for later timeframes. For HEV applications, the NiMH technology is based on the Toyota Prius battery pack, and the Li-ion technology is based on the 6-A h battery pack from Saft. For PHEV applications, the VL4M battery pack from Saft has been characterized. Because each vehicle is sized for both power and energy in the case of a PHEV, a sizing algorithm was developed to design the batteries specifically for each application [8]. To ensure that the battery has similar performance at the beginning and end of life, the packs were oversized both in power and energy, as shown in Figure. In addition, for PHEV applications, the state-of-charge (SOC) window (difference between maximum and minimum allowable SOC) was assumed to increase over time, allowing a reduction of the battery pack, as shown in Figure. Figure : Battery SOC Window Figures 2 and 3 show the cost of the battery packs for both high-power applications ($/kw) and high-energy applications ($/kwh). PHEV means the battery energy has been sized to have the ability to run miles all electric on the Urban Dynamometer Driving Schedule (UDDS). Figure 2: Cost Projections for High-Power Battery Figure : Battery Oversizing Figure 3: Cost Projections for High-Energy Battery

5 VEHICLE - As previously discussed, four vehicles classes were considered. Their characteristics are given in Table. Table : Vehicle Characteristics for Different Vehicle Classes Vehicle Class Glider Mass (Ref) (kg) Frontal Area (Ref) (m 2 ) Tire Wheel Radius (m) Midsize car P95/65/R5.37 Small SUV 2.52 P225/75/R Midsize SUV P235/7/R6.367 Figure 5: Frontal Area Reductions Pickup P255/65/R Because of improvements in vehicle material, the glider mass is expected to significantly decrease over time. The maximum value of 3% was defined on the basis of previous studies [9] that calculated the weight reduction that one could achieve when replacing the entire chassis frame by aluminum. Although the frontal area is expected to differ from one vehicle configuration to another (i.e., the electrical components will require more cooling capabilities), the values were considered constant across the technologies. Figures 4 and 5 show the reduction in both glider mass and frontal area. VEHICLE POWERTRAIN ASSUMPTIONS All the vehicles have been sized to meet the same requirements: km/h in 9 ±. s Maximum grade of 6% at 5 km/h for gross vehicle weight Maximum vehicle speed of >6 km/h For all cases, the engine or fuel cell powers are sized to perform the grade requirement without any assistance from the battery. For HEVs, the battery was sized to recuperate the entire braking energy during the UDDS drive cycle. For the PHEV case, the battery power is defined to be able to follow the UDDS in the electric mode while its energy is calculated to follow the trace for a specific distance. Because of the many vehicles considered, an automated sizing algorithm was defined []. Input-mode power split configurations, similar to those used in the Toyota Camry, were selected for all HEV and PHEV applications. The series fuel cell configurations use a two-gear transmission to achieve the maximum vehicle speed requirement. The vehicle-level control strategies employed for each configuration have been defined in previous publications [, 2, 3, 4, 5]. COMPONENT SIZING Figure 4: Glider Mass Reductions Figure 6 shows the evolution of both gasoline (SI) and hydrogen (H2) engine powers as a function of vehicle mass for a conventional midsize vehicle. As evident, the power for the hydrogen engine jumps significantly above 7 kg; this result is due to a change in technology (from port injected to direct injected).

6 5 4 ICE Power vs Vehicle mass for Midsize SI Conv H2 Conv 3 Power in kw Mass in kg 4 3 Figure 6: Evolution of ICE Power with Mass of Midsize Vehicle Figure 7 shows the engine and fuel cell system power as a function of vehicle mass for several advanced technologies, including HEVs and PHEVs. Since the electric machines used for PHEVs have higher power than the ones for HEVs, the engine is only sized for the gradeability requirement for PHEVs while it is also sized by performance for both power split and fuel cell HEVs. As a result, both engine and fuel cell powers decrease from HEVs to PHEVs. Power in kw SI Conv SI Split HEV SI Split PHEV H2 Split HEV H2 Split PHEV FC HEV FC PHEV ICE Power vs Vehicle mass for Midsize Figure 8: Fuel Cell Power for PHEV Midsize Cars FUEL EFFICIENCY ANALYSIS The vehicles were simulated on both the UDDS and HWFET drive cycles. The fuel consumption values and ratios presented below are based on unadjusted values in liters per km. The cold-start penalties were defined for each powertrain technology option on the basis of available data collected at Argonne s dynamometer facility and available in the literature. The following cold-start penalties (on the 55th cycle at 2 C) were maintained constant throughout the timeframes: Conventional: 5% Split HEV: 8% Split PHEV: 4% Fuel Cell HEV: 25% Fuel Cell PHEV: 5% Electric Vehicle: % EVOLUTION OF H2-ICE TECHNOLOGY - Figure 9 shows the evolution of the hydrogen engine technology. It indicates that significant improvements are expected in the future (up to 5%) Mass in kg Figure 7: ICE Power as a Function of Vehicle Mass for Different Configurations of Midsize Vehicle Figure 8 provides additional details regarding the fuel cell power for fuel cell PHEVs. The fuel cell power decreases with timeframe as the vehicle becomes lighter and the components more efficient.

7 . Ratio FCons gas eq for Midsize vs Split HEV H2 Ref Ratio FCons gas eq for Midsize vs Split HEV SI same year Figure 9: Ratio Fuel Consumption Gasoline the Hydrogen ICE HEV Reference Case for Midsize Cars EVOLUTION OF FUEL CELL TECHNOLOGY - Figure 2 show the evolution of the fuel cell technology. Since the fuel cell is already efficient, the improvements are not as significant as for the hydrogen engine (~3% reduction for the average case in ). Evolution Figure 2: Ratio Fuel Consumption Gasoline the Fuel Cell HEV Reference Case for Midsize Cars EVOLUTION OF H2-ICE VS. GASOLINE HEV - Figure 2 shows the evolution of HEVs for both hydrogen and gasoline engines. The current H2-ICE technology consumes slightly more than the gasoline HEV. However, when the direct injection technology is used, the fuel efficiency becomes higher for the hydrogen than the gasoline HEV. Figure 2: Ratio of Fuel Consumption Gasoline the Gasoline HEV (same year, same case, midsize car) EVOLUTION OF FUEL CELL VS. GASOLINE HEV - In 28, fuel cell HEVs consume about 49% less fuel than gasoline conventional vehicles (Figure 22). This difference in fuel consumption increases in the next timeframes to reach 54% for the average case. In, the trend changes. In the average case, the fuel cell vehicle consumes 5% more fuel than the gasoline conventional vehicle. This value is still higher than for the reference year, which means that the gasoline conventional vehicle will not improve its fuel consumption as fast as the fuel cell HEV Ratio FCons gas eq for Small SUV vs Conv SI same year.3 Figure 22: Ratio of Fuel Consumption Gasoline the Gasoline Conventional Vehicle (same year, same case, small SUV) Whereas the ratios between fuel cell HEV and hydrogen power split HEV increase over time, owing to some

8 improvements in the powertrain, the same conclusion cannot be made for the comparison with the gasoline power split HEV (Figure 23). The fuel cell HEV goes from 26% better fuel consumption in 28 to 32% in the average case. From to, the ratio slightly increases, narrowing the difference in fuel consumption between the fuel cell HEV and gasoline power split HEV Ratio FCons gas eq for Small SUV vs Split HEV SI same year Figure 23: Ratio of Fuel Consumption Gasoline the Gasoline Power Split HEV (same year, same case, small SUV) EVOLUTION OF ICE VS. FUEL CELL HEV - The fuel consumption ratios between fuel cell vehicles and hydrogen conventional vehicles stay below.5 over all timeframes (Figure 24). This result means that the fuel consumption for the fuel cell vehicle is always at least twice as high as that of the hydrogen conventional vehicle. From 28 to 25, the fuel cell is approximately 55% better than the hydrogen ICE, but in the average case, this ratio rises to 56% due to the changes in hydrogen storage systems. Finally in the average case, the ratio increases to.47, indicating an improvement start for hydrogen conventional vehicles Ratio FCons gas eq for Small SUV vs Conv H2 same year Figure 24: Ratio of Fuel Consumption Gasoline the Hydrogen Conventional Vehicle (same year, same case, small SUV) The ratios for fuel cell HEVs in comparison to hydrogen power split HEVs differ completely from those of the hydrogen ICE. The ratios increase over time (Figure 25); this result is due to the faster improvement made by hydrogen power split HEVs compared to the fuel cell HEVs. In 28, the fuel cell vehicles consumed about 29% less fuel than hydrogen power split HEVs, but this advantage declines to 9% in the average case. This result confirms the trends described previously Ratio FCons gas eq for Small SUV vs Split HEV H2 same year Figure 25: Ratio of Fuel Consumption Gasoline the Hydrogen Power Split HEV (same year, same case, midsize car) COST ANALYSIS EVOLUTION OF H2-ICE VS. GASOLINE VEHICLE - Figure 26 shows the cost ratio between hydrogen engine vehicles and conventional gasoline vehicles. While hydrogen engines will remain more expensive, the technology will become more cost competitive over time. The main reason is cheaper hydrogen storage systems..3

9 Ratio Cost () Ratio Vehicle Cost AVG for Midsize vs Conv SI same year H2 Conv H2 Split HEV Ra tio C ost () FC HEV FC HEV PHEV FC HEV PHEV2 FC HEV PHEV3 FC HEV PHEV Figure 26: Cost Ratio between H2-ICE Vehicle and Conventional Gasoline Vehicle EVOLUTION OF FUEL CELL VS. GASOLINE HEV - Figure 27 shows the cost ratio between fuel cell and conventional gasoline vehicles. The trend is similar to that for the hydrogen engine in the sense that the cost ratio will decrease in the future. However, this decrease is more pronounced for the fuel cell HEV because in addition to a significant cost reduction for the hydrogen tanks, the vehicle also benefits from the cost reduction related to the fuel cell system. Ratio Cost () Ratio Vehicle Cost AVG for Midsize vs Conv SI same year Figure 28: Cost Ratio between H2-ICE HEV and Fuel Cell Vehicle TRADE-OFF BETWEEN FUEL EFFICIENCY AND COST The following focuses on analyzing the tradeoff between fuel efficiency and incremental cost. The reference used is the current gasoline conventional vehicle with a fuel consumption of 3. gal/ miles. Figure 29 shows the trade-off for hydrogen hybrids for different timeframes. The fuel consumption can be reduced from.6 to 5 gal/ miles for an additional cost ranging from $6 to $3. As one expects, the best fuel consumptions and lowest costs are achieved for the later timeframes (). Incremental Cost vs fuel consumption for Midsize H2 Split HEV Cost ($) Figure 27: Cost Ratio between Fuel Cell Vehicle and Conventional Gasoline Vehicle EVOLUTION OF H2-ICE VS. FUEL CELL HEV - Figure 28 shows the cost ratio comparison between hydrogen fueled vehicles (both engine and fuel cells). While the fuel cell vehicles are currently more expensive than their hydrogen engine counterparts (ratio of.38 for the fuel cell HEV in 28), the additional cost is reduced in the later timeframes. The results are due to a more significant decrease in cost reduction for the fuel cell system than for the hydrogen engine Fuel Consumption (gallons/mile) Figure 29: Trade-off between Fuel Efficiency and Cost for Midsize H2-ICE HEV Figure 3 shows the tradeoffs of incremental cost vs. fuel consumption for the fuel cell vehicles (HEV and PHEV) compared to the conventional gasoline vehicles. For the HEVs at gal/ miles, the additional cost is higher (ranges from $2, to $5) with the lowest fuel efficiency. For the PHEVs, we find a diminishing

10 return on investments since little fuel efficiency gain is achieved for higher all-electric range for a higher cost. 4 x 4 Figure 3 shows the trade-off between fuel efficiency and cost for all the hydrogen fueled vehicles. The figure shows how the same fuel efficiency can be achieved with different technologies at different cost. Incremental Cost vs fuel consumption for Midsize Fuel Cell Cost ($) Dark Blue = FC HEV Green = FC PHEV Yellow = FC PHEV2 Red = FC PHEV3 Light Blue = FC PHEV Fuel Consumption (gallons/mile).6.4 Figure 3: Trade-off between Fuel Efficiency and Cost for Midsize Fuel Cell Vehicles 3 x 4 Incremental Cost vs fuel consumption for Hydrogen Midsize Cost ($).5 Dark Blue = Conv Green = Split HEV Yellow = Split PHEV Red = Split PHEV2 Light Blue = Split PHEV3 Purple = Split PHEV Fuel Consumption (gallons/mile).5 Figure 3: Trade-off between Fuel Efficiency and Cost for Midsize Hydrogen Fueled Vehicles

11 CONCLUSIONS The potential fuel economy of two promising hydrogen technologies has been compared on the UDDS and HWFET driving cycles for several vehicle classes and timeframes (28 to ). The uncertainties of each technology were taken into account as part of the evaluation. The necessary developments to achieve the respective efficiency and cost goals are significant. The fuel efficiency of hydrogen vehicles is expected to significantly improve in the future. While the improvements for the ICE-powered vehicles are related to engine enhancements, most gains from the fuel cell vehicles are related to the overall vehicle. Most improvements for the fuel cell vehicle are related to cost, with significant reductions expected for both the fuel cell system and the hydrogen storage in later years. The study confirms the Department of Energy (DOE) position that while fuel cell vehicles consistently achieve the highest fuel efficiency, H2-ICE can serve as a bridging technology and might help in the development of the infrastructure needed for hydrogen fuel. ACKNOWLEDGMENTS This work was supported by DOE s FreedomCAR and Vehicle Technology Office under the direction of Lee Slezak and Gurpreet Singh. The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory ( Argonne ). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC2-6CH357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government. REFERENCES. Department of Energy, Office of Energy Efficiency and Renewable Energy, Planning, Budget, and Analysis, 28_benefits.html 2. Argonne National Laboratory, PSAT (Powertrain Systems Analysis Toolkit), anl.gov. 3. Rousseau, A., Sharer, P., and Besnier, F., Feasibility of Reusable Vehicle Modeling: Application to Hybrid Vehicles, SAE paper , SAE World Congress, Detroit, March Wallner, T., and Lohse-Busch, H., Performance, Efficiency, and Emissions Evaluation of a Supercharged, Hydrogen-Powered, 4-Cylinder Engine, SAE paper 27--6, SAE Fuels and Emissions Conference, South Africa, January Bohn, T., and Duoba, M., Implementation of a Non- Intrusive In-Vehicle Engine Torque Sensor for Benchmarking the Toyota Prius HEV, SAE paper , SAE World Congress, Detroit, April Bandel, W., The Turbocharged GDI Engine: Boosted Synergies for High Fuel Economy Plus Ultra-Low Emissions, SAE paper , SAE World Congress, Detroit, April Olszewski, M., Evaluation of the 27 Toyota Camry Hybrid Synergy Drive System, ORNL/TM- 27/9, January Sharer, P., Rousseau, A., Nelson, P., and Pagerit, S., Vehicle Simulation Results for PHEV Battery Requirements, 22th International Electric Vehicle Symposium (EVS22),Yokohama, October Stodolsky, F., and Vyas, A., Life-Cycle Energy Savings Potential from Aluminum-Intensive Vehicles, 995 Total Life Cycle Conference & Exposition, Vienna, October Freyermuth, V., Fallas, E., and Rousseau, A., Comparison of Powertrain Configuration for Plug-in HEVs from a Fuel Economy Perspective, SAE paper , SAE World Congress, Detroit, April 28.. Rousseau, A., Sharer, P., Pagerit, S., and Duoba, M., Integrating Data, Performing Quality Assurance, and Validating the Vehicle Model for the 24 Prius Using PSAT, SAE paper , SAE World Congress, Detroit, April Pagerit, S., Rousseau, A., and Sharer, P., Global Optimization to Real Time Control of HEV Power Flow: Example of a Fuel Cell Hybrid Vehicle, 2th International Electric Vehicle Symposium (EVS2), Monaco, April Sharer, P., Rousseau, A., Karbowski, D., and Pagerit, S., Plug-in Hybrid Electric Vehicle Control Strategy: Comparison between EV and Charge- Depleting Options, SAE paper , SAE World Congress, Detroit, April Cao, Q., Pagerit, S., Carlson, R., and Rousseau, A., PHEV Hymotion Prius Model Validation and Control Improvements, 23rd International Electric Vehicle Symposium (EVS23), Anaheim, CA, December Karbowski, D., Rousseau, A., Pagerit, S., and Sharer, P., Plug-in Vehicle Control Strategy: From Global Optimization to Real Time Application, 22th International Electric Vehicle Symposium (EVS22), Yokohama, October 26. CONTACT Aymeric Rousseau Center for Transportation Research (63) arousseau@anl.gov