A PEMFC multi-physical model to evaluate the consequences of parameter uncertainty on the fuel cell performance

•A method is proposed to help evaluating the reliability of a PEMFC.•The objective is to guarantee a minimal level of electrical performance for the cell.•The method uses a close coupling between physical modeling and statistical analysis.•Some statistical distributions are considered for the model input parameters.•The cell performance sensitivity is determined according to the input uncertainty.

In this article, a novel method is proposed to help evaluating the reliability of a Proton Exchange Membrane Fuel Cell (PEMFC) stack. The aim is to guarantee a target level of electrical performance that can be considered as sufficient to meet any application requirements. The approach is based on the close coupling between physical modeling and statistical analysis of reliability. The complexity of the physical phenomena involved in the fuel cell is taken into account through the development of a dynamical, symbolic, acausal modeling tool including physical and semi-empirical parameters as well. The proposed knowledge PEMFC model is one-dimensional, non-isothermal and it includes a two-phase fluidic flow representation (each reactant is considered as a mix of gases and liquid water). The modeling is implemented using the DYMOLA software; one of the advantages of this simulation tool is that it allows an effective connection between multi-physical modeling and statistical treatments. In this perspective, the modeling is done with the aim of having as much relevant physical parameters as possible. The different effects of these parameters on the PEMFC electrical behavior can be observed and the performance sensitivity can be determined considering statistical distributions of input parameters, which is a step towards reliability analysis.

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