A framework for the probabilistic analysis of PEMFC performance based on multi-physical modelling, stochastic method, and design of numerical experiments. (5th January 2017)

• Record Type: Journal Article
• Authors: Noguer, N.; Candusso, D.; Kouta, R.; Harel, F.; Charon, W.; Coquery, G.
• Is Part Of: International journal of hydrogen energy. Volume 42:Number 1(2017)
• Page Start: 459
• Page End: 477
• Publication Date: 2017-01-05
• Subjects: PEM fuel cell -- Reliability -- Statistical analysis -- Design of experiments; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2016.11.074
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: In this article, a probabilistic approach is applied to evaluate the impact of the GDL porosity uncertainty on the electrical performances of a PEMFC. The study is based on the use of a dynamical, symbolic, and acausal knowledge model. Some statistical distributions are introduced on the input model parameter (porosity) and the statistical distributions induced on the output parameters (cell voltage, resistance) are analyzed. The difference observed between the shapes of the input and output distributions (respectively some Gaussian and inverse Gamma distributions with a threshold phenomenon) is the result of strong nonlinearities linked with the integration of multiphase flow phenomena in the modelling (e.g. diffusion limit of the humidified air in the GDL). The study is also conducted for different conditions of temperature and pressure through a design of numerical experiments. One of the results obtained is that the variation coefficient related to the GDL porosity has, compared to the other parameters with their intervals of variation considered, little effect on the average output distributions. However, the dispersion introduced on the porosity impacts their shapes (e.g. significant effect on the standard deviation). Graphical abstract: Highlights: Probabilistic approach for the analysis of fuel cell performance and reliability. Integration of uncertainty on GDL porosity into a knowledge PEMFC model. Uncertainty on porosity represented by Gaussian probability distributions. Inverse Gamma distributions with threshold phenomenon observed for voltage outputs. Significant impact of GDL porosity dispersion on shapes of voltage distributions.