Moving Horizon Estimation Based Nonlinear Economic Model Predictive Control Method for Fuel Cell Air Supply Subsystem

This research introduces a nonlinear economic model predictive control(NEMPC) strategy based on moving horizon estimation(MHE), for the proton exchange membrane fuel cell (PEMFC) system. The proposed strategy avoids oxygen starvation phenomenon and enhances the net power of the fuel cell systems. This strategy employs the NEMPC method to deal with nonlinear multiple input multiple output fuel cell systems and incorporates MHE to improve the robustness of the algorithm. The multiple shooting method is also used to expedite the computational speed of the algorithm. To investigate the impacts of the proposed strategy on the fuel cell systems, the operation characteristics of the fuel cell and the output net power of the system are analyzed under the simulation condition of pulse current. The results show that the proposed algorithm can guarantee the normal operation of the cathode side of the fuel cell systems and increase the output power of the dynamic response of the fuel cell system by 2.34% compared with the MHE based NMPC.