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The optimal operation of fuel cells in changing environmental and variable load conditions requires mathematical modeling. The electrochemical behavior of polymer electrolyte membrane fuel cells (PEMFC) is commonly described with a semi‐empirical model requiring fuel cell specific model parameter values. A large number of different nature inspired, heuristic optimization methods have been proposed...
The target in this paper is to show how Genetic Algorithms apply for parameter identification of different fuel cells. Therefore, two electrochemical models have been fitted for three different fuel cells. The data originates in the current vs. voltage curves (polarization curves) from the published literature. The results seem promising - a real-coded Genetic Algorithm seems to provide with the model...
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