Stair-like generalized predictive control for improving the output power of proton exchange membrane fuel cell system

The air supply system has the great influence on the output power of Proton Exchange Membrane fuel cell system. In this paper a stair-like generalized predictive control algorithm based on multiple models switching is proposed to regulate the inlet flow rate of air for improving the output power of fuel cell system. A multiple models bank contains several fixed models and an adaptive model is used to describe the air supply system, and the best model can be selected by the optimal error functions and model switching rules. Then a stair-like generalized predictive controller is designed based on this model to control the oxygen excess ratio by adjusting the air inlet flow rate so as to improve the output power of system. The simulation results demonstrate that the proposed algorithm can raise the output power of fuel cell system, and has the better performance than traditional generalized predictive control with signal adaptive model.