LPV Model-Based Fault Diagnosis Using Relative Fault Sensitivity Signature Approach in a PEM Fuel Cell.

Abstract

In this paper, the problem of fault diagnosis in a PEM Fuel Cell (PEM FC) system using a model-based approach is addressed. A Linear Parameter Varying (LPV) model is used to catch the non linear dynamics of the PEM FC. A new fault diagnosis method is proposed based on structured residuals generation and sensitivity analysis evaluation. Robustness in fault diagnosis is increased by use of a relative fault sensitivity approach. The proposed methodology is applied to a Polymer Electrolyt Membrane Fuel Cell system. Finally, simulation results using the proposed approach presents a better isolability performance than classical Boolean fault signature approach.