Optimization of proton-exchange membrane fuel cells model by developed design of horse optimizer

The present research suggests a new method for optimum parameters identification of the unknown parameters of the proton-exchange membrane fuel cells (PEMFCs). The technique is defined by proposing an improved bio-inspired technique, which is developed Horse Optimization Algorithm which is used for optimum model identification of PEMFCs. The target here is to provide higher confirmation of the empirical outputted data points and the model outputted voltage. It is done by minimizing the mean square error of the two output values. To specify the efficiency of the proposed technique, this has been executed to a 250 W PEM fuel cell stack model from the literature and the achievements have been put in comparison with several latest techniques to indicate the efficiency of the method technique. Simulation results showed that the proposed technique with 1.2512 MSE delivers the maximum confirmation against the comparative techniques that have been utilized as an effective method for the PEMFC model identification.