The fuel cell (FC) is at present the alternative solution to the fossil fuels the most promising. It is however advisable to improve its reliability. This requires the implementation of algorithms capable of estimating in real time the state of health and forecasting its remaining useful life (prognostics). The methods of prognostics based on a physical model offer precise results once they do not requiring either learning or expertise of the operator. However, the problem for a FC system lies in the coupling of several physical phenomena, the uncertainty of the parameters of the model and the low instrumentation of the FC stack. Thus, we use uncertain models based on the Bond Graph tool well adapted for the FC. Concretely, the parameters uncertainties are integrated in the model of evolution of the powers which is used for the detection of the beginning of the aging and the estimation of the degradation of the FC based on the causal and structural properties of the model. The generated model of degradation is used by an extended Kalman filter which allows the estimation of the state of health , the dynamics of the aging and the quantification of the uncertainty for any operating condition (of temperature, current and pressure). An Inverse First Order Reliability Method is then used for the prediction of the remaining useful life and the inherent uncertainty. The global method was validated on various sets of experimental data. Thanks to this set of tools, a control based on the inversion of an Energetic Macroscopic Representation (EMR) model with time varying parameters, robust to aging is developed based on the state of health estimation.
Directeurs de thèse: Pr. Belkacem OULD BOUAMAMA (Université de Lille 1) et Pr. Daniel HISSEL (Université de Bourgogne Franche-Comté) Encadré par Pr. Mickaël HILAIRET (Université de Bourgogne Franche-Comté) Rapporteurs: Pr. Rachid OUTBIB (Aix-Marseille Université), Pr. Guy CLERC (Université Claude Bernard Lyon 1) Examinateurs : MCF – HDR Rafael GOURIVEAU (ENSMM Besançon), Pr. Alain RICHARD (Université de Lorraine Nancy), Pr. Geneviève Dauphin-Tanguy (Ecole Centrale de Lille)
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