Abstract
Our recent analytical model of direct methanol fuel cell is used to fit experimental performance curves. Based on evolutionary genetic algorithm, a new fitting procedure is developed. The idea is to fit simultaneously a set of performance curves, which have several common fitting parameters. On the first stage of evolution all parameters are determined independently. Starting from certain step a mean values of common parameters are calculated and further evolution corrects the mean values. For different sets of experimental curves the method gives well reproducible results. The physical parameters resulted from fitting and the effect of crossover on cell performance are discussed.
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