Precise parameter estimation of PEM fuel cell via weighted mean of vectors optimizer

This paper deals with the determination of the optimal values to be given for the seven unknown parameters of the proton exchange membrane fuel cell (PEMFC). To this end, the weighted mean of vectors optimizer (INFO) metaheuristic algorithm is applied to estimate these parameters by minimizing the sum of squared errors (SSEs) between the measured and calculated voltages of the PEMFC. Three commercial types of PEMFCs are investigated: (i) BCS 500 W Stack, (ii) NedStack PS6 Stack, and (iii) Horizon 500 W Stack. The accuracy of the applied INFO algorithm is verified by comparing the estimated voltage–current \((I-V)\) $(I-V)$ characteristics with the measured data. Furthermore, the estimated parameters of electrical PEMFCs, the minimum reached SSE, and the standard deviation Std values achieved by INFO are compared with the results obtained using other competitive metaheuristic optimization algorithms such as Honey badger algorithm, Gradient-based optimizer, Harris hawks optimization, and others. From the obtained results, the convergence curves show that the unknown parameters of the three PEMFCs are better estimated using the proposed INFO than other algorithms.