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Fuel cell hybrid electric vehicles (FCHEVs) composed of fuel cells and batteries can improve the dynamic response and durability of vehicle propulsion. In addition, braking energy can be recovered by batteries. The energy management strategy (EMS) for distributing the requested power through different types of energy sources plays an important role in FCHEVs. Reasonable power split not only improves vehicle performance but also enhances fuel economy. In this paper, considering the power tracking control strategy which is widely adopted in Advanced Vehicle Simulator (ADVISOR), a constrained nonlinear programming parameter optimization model is established for minimizing fuel consumption. The principal parameters of power tracking control strategy are set as the optimized variables, with the dynamic performance index of FCHEVs being defined as the constraint condition. Then, the genetic algorithm (GA) is applied in the control strategy design for solving the optimization problem.

This paper is contributed to determining model parameters for DMFCs. Theoretical evaluations are carried out to set up the relationship between the unknown and measurable parameters or variables. A laboratory-scale liquid-feed cell was simulated under different operating conditions. The resulting measurable static performance curves are used as basic information. Some key kinetic and physical parameters can be determined or estimated for a DMFC model.