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Optimum modeling of proton exchange membrane (PEM) fuel cell has become the major focus of various researches. The main drawback in optimum modeling is that the model parameters are unknown, and empirical values are not sufficient to exactly model it. Since the characteristic of a PEM fuel cell is highly nonlinear, an excellent optimization technique is needed. In this paper, an innovative global harmony search (IGHS) algorithm-based parameter identification method is proposed. The IGHS algorithm is employed for parameter identification of the SR-12 Modular PEM Generator, the Ballard Mark V FC, and the BCS 500-W stack, and its performance is compared with that of two versions of harmony search algorithms, three versions of particle swarm optimization algorithms, bee swarm optimization algorithm, and seeker optimization algorithm. Simulation results reveal that the proposed technique gives both better and more robust results than the other studied algorithms.