A Novel Hybrid Intelligent Control Approach for Proton Exchange Membrane Fuel Cell Air-Feeding System

Under the rapid development of clean energy, proton exchange membrane fuel cell (PEMFC) has become a keyway for energy transformation. The precise control of the oxygen excess ratio (OER) is crucial to ensure the stable operation of the PEMFC system. Therefore, effective control for the cathode air-feeding system is of vital significance for PEMFC power generation. In the face of sudden changes in PEMFC load, a selftuning Proportional-Integral-Derivative (PID) controller based on hybrid intelligent algorithm has been proposed, to ensure the cathode air-feeding system operation. The hybrid intelligent algorithm is based on particle swarm optimization (PSO) algorithm combined with chaos theory to optimize the PID parameters offline. The results indicate that the designed controller has better convergence, and less time lag compared to other controllers and 40% improvement compared to classical PID controller. This control approach improves performance and stability of PEMFC aiming to amplify the fuel cell application.