Proton Exchange Membrane Fuel Cell Model Optimization Based on Seeker Optimization Algorithm

Seeker optimization algorithm (SOA) which mimicked the stochastic searching behavior of human was applied to continuous space of swarm intelligence. According to the modeling principle of proton exchange membrane fuel cell (PEMFC) polarization curve model, SOA was proposed to research a set of optimized parameters in the PEMFC polarization curve model. The comprehensive comparison between simulation results and experimental results demonstrate that SOA can make the simulation results fitted the experiment data with higher precision and has manifest superiority for optimizing PEMFC polarization curve model. Therefore, SOA makes important effect for improving the performance of PEMFC polarization curve model and becomes a new effective tool in the fields of model optimization.