System-Level Model and Stochastic Optimal Control for a PEM Fuel Cell Hybrid Vehicle

System-level modeling and control strategy development for a fuel cell hybrid vehicle (FCHV) are presented in this paper. A reduced-order fuel cell model is created to accurately predict the fuel cell system efficiency while retaining dynamic effects of important variables. The fuel cell system model is then integrated with a DC/DC converter, a Li-ion battery, an electric drive, and tire/vehicle dynamics to form an FCHV. In order to optimize the power management strategy of the FCHV, we develop a stochastic design approach based on the Markov chain modeling and stochastic dynamic programming (SDP). The driver demand is modeled as a Markov process to represent the future uncertainty under diverse driving conditions. The infinite-horizon SDP solution generates a stationary state-feedback control policy to achieve optimal power management between the fuel cell system and battery. Simulation results over different driving cycles are presented to demonstrate the effectiveness of the proposed stochastic approach.