An appropriate mathematical model can help researchers to simulate

evaluate

and control a proton exchange membrane fuel cell (PEMFC) stack system. Because a PEMFC is a nonlinear and strongly coupled system

many assumptions and approximations are considered during modeling. Therefore

some differences are found between model results and the real performance of PEMFCs. To increase the precision of the models so that they can describe better the actual performance

optimization of PEMFC model parameters is essential. In this paper

an artificial bee swarm optimization algorithm

called ABSO

is proposed for optimizing the parameters of a steady-state PEMFC stack model suitable for electrical engineering applications. For studying the usefulness of the proposed algorithm

ABSO-based results are compared with the results from a genetic algorithm (GA) and particle swarm optimization (PSO). The results show that the ABSO algorithm outperforms the other algorithms.