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Communication Dans Un Congrès Année : 2017

Data-driven multi-fault approach for H2/O2 PEM FuelCell diagnosis

Résumé

Proton Exchange Membrane Fuel Cells (PEMFCs) are promising devices in energy conversion domain. Improper operating conditions can severely affect their performance. Particularly, improper water management, fuel quality and reactants starvation conditions, if recurrent or continued for a long period can have critical effects, introducing degradations phenomena and reducing the FC lifespan. This work aims to investigate the impact of improper water managements and reactants starvation conditions on stack voltage and Electrochemical Impedance Spectroscopy (EIS) measurements for multi-fault detection purposes. In-house tests performed on H2/O2 PEMFC short-stacks performance are presented. Data are then analyzed and processed through a double-fuzzy multi-fault detection approach. The procedure can be also used for H2/Air PEMFC diagnosis. Experimental data and data-driven multifault detection procedure improvement are developed in the framework of the European Project Health-code.
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Dates et versions

hal-01764611 , version 1 (12-04-2018)

Identifiants

  • HAL Id : hal-01764611 , version 1

Citer

Raphaëlle Petrone, Elodie Pahon, Fabien Harel, Samir Jemei, Didier Chamagne, et al.. Data-driven multi-fault approach for H2/O2 PEM FuelCell diagnosis. IEEE VPPC'2017 Conference. Vehicle Power and Propulsion Conference, Dec 2017, BELFORT, France. ⟨hal-01764611⟩
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