Thermal Management of Open-Cathode PEMFC Based on NMPC and EKF

The purpose of this study is to design a thermal management algorithm for open-cathode proton exchange membrane fuel cell (PEMFC). A nonlinear model predictive control (NMPC) method is proposed for controlling the duty cycles of cooling fans. The electrochemical and thermal models of the open-cathode PEMFC are initially constructed. A further nonlinear control model is then developed based on the simplified fuel cell model. The system state variables are subsequently observed using the extended Kalman filter (EKF) method which are used as state inputs of NMPC. Finally, the fuel cell model, NMPC and EKF are constructed based on SIMULINK, and three simulations are conducted to assess the control effect. These simulations involved tracking constant temperature under constant current, tracking constant temperature under dynamic current, and tracking dynamic temperature under constant current, respectively. The results demonstrated that the control effect is superior to that of the PID algorithm in terms of tracking accuracy, response speed and robustness.