Prognostics of PEM fuel cell in a particle filtering framework
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- 作者：Marine Jouin ; Rafael Gouriveau ; Daniel Hissel ; Marie-C茅cile P茅ra ; Noureddine Zerhouni
- 关键词：Proton exchange membrane (PEM) fuel cell ; Prognostics ; Remaining useful life ; PHM ; Particle filter
- 刊名：International Journal of Hydrogen Energy
- 出版年：2 January, 2014
- 年：2014
- 卷：39
- 期：1
- 页码：481-494
- 全文大小：1680 K
文摘
Proton Exchange Membrane Fuel Cells (PEMFC) suffer from a limited lifespan, which impedes their uses at a large scale. From this point of view, prognostics appears to be a promising activity since the estimation of the Remaining Useful Life (RUL) before a failure occurs allows deciding from mitigation actions at the right time when needed. Prognostics is however not a trivial task: 1) underlying degradation mechanisms cannot be easily measured and modeled, 2) health prediction must be performed with a long enough time horizon to allow reaction. The aim of this paper is to face these problems by proposing a prognostics framework that enables avoiding assumptions on the PEMFC behavior, while ensuring good accuracy on RUL estimates. Developments are based on a particle filtering approach that enables including non-observable states (degradation through) into physical models. RUL estimates are obtained by considering successive probability distributions of degrading states. The method is applied on 2 data sets, where 3 models of the voltage drop are tested to compare predictions. Results are obtained with an accuracy of 90聽h聽around the real RUL value (for a 1000聽h聽lifespan), clearly showing the significance of the proposed approach.