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.
Issue Section:
Technical Papers
Keywords:
hybrid electric vehicles,
fuel cell vehicles,
proton exchange membrane fuel cells,
optimal control,
Markov processes,
reduced order systems,
vehicle dynamics,
dynamic programming,
infinite horizon,
state feedback,
fuel cell hybrid vehicle,
power management strategy,
stochastic optimal control
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.Copyright © 2006
by American Society of Mechanical Engineers
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