An optimized fuzzy PI control method utilizing the IGWO algorithm for the ejector-based hydrogen recirculation PEMFC system

Research on modeling and control strategies of proton exchange membrane fuel cell (PEMFC) system is pivotal for enhancing their performance and operational lifespan. In this study, the anode pressure control challenge within the hydrogen recirculation system of fuel cells is tackled by proposing a fuzzy PI control method optimized with an improved grey wolf optimization (IGWO) algorithm. Initially, a dynamic model of the ejector-based hydrogen recirculation PEMFC system is developed. To address the tendency that the traditional GWO algorithm falls into local optima, enhancements including an adjusted convergence factor and the integration of Gaussian mutation and a greedy algorithm are introduced, which are then applied to optimize the parameters of the fuzzy PI controller. By utilizing MATLAB/Simulink platform, a model for the PEMFC hydrogen recirculation system is developed and subjected to simulation studies. The results of the simulation suggest that, compared to traditional PID and fuzzy PI controllers, the proposed method shows improvements in terms of settling time (less than 1 s) and overshoot (less than 1%), along with enhanced robustness, Ensuring the sustained and dependable operation of the PEMFC over the long term.