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The scope of this study is to optimize the powertrain of a fuel cell powered hybrid electric vehicle and plug-in hybrid electric vehicle, aiming to minimize the cost, minimize fuel consumption, and maximixe all-electric range (AER). A genetic algorithm (GA) was used to perform single objective optimization, and a non-dominated sorting genetic algorithm (NSGA-II) to perform multi-objective optimization. Both algorithms were programmed in MATLAB. The cost, fuel consumption and AER were optimized by the GA individually, and the couples cost and fuel consumption, and cost and AER, were evaluated by the NSGA-II. In order to optimize the vehicle powertrain, not only the fuel cell, electric motor, and battery, are sized but different component models are also considered, including different battery chemistries (Lithium and Nickel-metal hydride). The battery charge sustaining level is also an optimization variable.