Optimal parameter identification of adaptive fuzzy logic MPPT based-bald eagle search optimization algorithm to boost the performance of PEM fuel cell

The output power of proton exchange membrane (PEM) fuel cell is dependent on operating temperature and the membrane water content. Changing the operation condition changes the location maximum power point (MPP) on the nonlinear curve of power versus the current. Therefore, a robust MPP tracking strategy is obligatory to grantee the work of PEM fuel cell around or close the MPP and boost the harvested energy. The suggested tracker is based on the bald eagle search (BES) optimization algorithm to identify the best values to entirely advantage the inherent flexibility of fuzzy logic control (FLC) system furthermore to accomplish rapid and precise tracking. Throughout the optimization procedure, the gains of membership functions of FLC are assigned to be decision variables, while the integral of error is the objective function. To approve the advantage of BES, a comparison with gradient-based optimizer (GBO), osprey optimization algorithm (OOA), particle swarm optimization (PSO), pelican optimization algorithm (POA), blue monkey algorithm (BMA) and henry gas solubility optimization (HGS) is performed. The BES has the highest performance compared with other optimizers; it achieves the best value of 1.7638 flowed by GBO (1.7667) whereas the worst value of 1.7987 is obtained by POA. Additionally, the lowest STD of 0.0046 is achieved by BES followed by GBO (0.0078) whereas the worst value of STD of 0.0243 is obtained by HGS. Finally, the optimized FLC-MPPT-based BES is compared with commonly MPPTs including classical FLC and perturb & observe in terms of dynamic and steady state conditions. The comparison demonstrated that the suggested FLC-MPPT-based BES has fast tracking speed and diminishes the oscillations around MPP in steady state.