PEM Fuel Cell Parameters Identification Based on Grey Wolf Optimization Algorithm

Proton exchange membrane fuel cells are one of the best devices that can replace energy sources based on fossil fuels. Therefore, the modeling of fuel cells is essential for developing and analyzing this phenomenon. In this work, we will model a PEMFC NEXA 1200W based on GWO, grey wolves’ optimization. The aim will be to find the optimal parameters for a model that will give the smaller value of the SSE, sum of square errors, calculated from the actual output voltage of NEXA 1200 W and the voltage of the simulated model. Our work is based on two combined models: the first is a mathematical model of the PEMFC that enables the calculation of the output voltage related to some variables and parameters. In contrast, the second one is exploited to calculate the instantaneous Temperature used as an input Temperature of the PEMFC model.