Prognostics of PEM fuel cell in a particle filtering framework.

Marine Jouin (1) , Rafael Gouriveau (1) , Daniel Hissel (1) , Marie-Cécile Péra (1) , Noureddine Zerhouni (1)

1 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)

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 time) 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 hours around the real RUL value (for a 1000 hours lifespan), clearly showing the significance of the proposed approach.

Domaines: Automatique / Robotique

Marine Jouin, Rafael Gouriveau, Daniel Hissel, Marie-Cécile Péra, Noureddine Zerhouni. Prognostics of PEM fuel cell in a particle filtering framework.. International Journal of Hydrogen Energy, 2014, 39 (1-2), pp.481-494. ⟨hal-00903643⟩