Modeling and optimization for proton exchange membrane fuel cell stack using aging and challenging P systems based optimization algorithm

Accurate models of PEM (proton exchange membrane) fuel cells are of great significance for the analysis and the control for power generation. We present a new semi-empirical model to predict the voltage outputs of PEM fuel cell stacks. We also introduce a new estimation method, called AC-POA (aging and challenging P systems based optimization algorithm) allowing deriving the parameters of the semi-empirical model. In our model, the cathode inlet pressure is selected as an additional factor to modify the expression of concentration over-voltage V_con for traditional Amphlett's PEM fuel cell model. In AC-POA, the aging-mechanism inspired object updating rule is merged in existing P system. We validate through experiments the effectiveness of AC-POA and the fitting accuracy of our model. Modeling comparison results show that the predictions of our model are the best in terms of fitting to actual sample data.