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Parameter extraction from experimental PEFC data using an evolutionary optimization algorithm

  • M. Zaglio (a1), G. Schuler (a1), A. Wokaun (a1), J. Mantzaras (a2) and F. N. Büchi (a1)...

Abstract

The accurate characterization of the parameters related to the charge and water transport in the ionomer membrane of polymer electrolyte fuel cells (PEFC) is highly important for the understanding and interpretation of the overall cell behavior. Despite the big efforts to experimentally determine these parameters, a large scatter of data is reported in the literature, due to the inherent experimental difficulties. Likewise, the porosity and tortuosity of the gas diffusion layers affect the membrane water content and the local cell performance, but the published data are usually measured ex-situ, not accounting for the effect of clamping pressure. Using a quasi two-dimensional model and experimental current density data from a linear cell of technical size, a multiparameter optimization procedure based on an evolutionary algorithm has been applied to determine eight material properties highly influencing the cell performance. The optimization procedure converges towards a well defined solution and the resulting parameter values are compared to those available in the literature. The quality of the set of parameters extracted by the optimization procedure is assessed by a sensitivity analysis.

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Parameter extraction from experimental PEFC data using an evolutionary optimization algorithm

  • M. Zaglio (a1), G. Schuler (a1), A. Wokaun (a1), J. Mantzaras (a2) and F. N. Büchi (a1)...

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