Model-based aging tolerant control with power loss prediction of Proton Exchange Membrane Fuel Cell

Proton Exchange Membrane Fuel Cells are promising energy converters that allow powering vehicles or buildings in a clean manner. Nevertheless, their performance are affected by faults and irreversible degradation mechanisms that are far from being fully understood. Consequently, during the last deca...

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Bibliographic Details
Published in:International journal of hydrogen energy Vol. 45; no. 19; pp. 11242 - 11254
Main Authors: Bressel, Mathieu, Hilairet, Mickael, Hissel, Daniel, Ould Bouamama, Belkacem
Format: Journal Article
Language:English
Published: Elsevier Ltd 03.04.2020
Elsevier
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ISSN:0360-3199, 1879-3487
Online Access:Get full text
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Summary:Proton Exchange Membrane Fuel Cells are promising energy converters that allow powering vehicles or buildings in a clean manner. Nevertheless, their performance are affected by faults and irreversible degradation mechanisms that are far from being fully understood. Consequently, during the last decade, researches have been conducted on the diagnostic of faults of this promising converter. Nevertheless, aging was never the subject of a particular attention concerning control. As a result, this paper proposes an aging tolerant control strategy for Proton Exchange Membrane Fuel Cells. It aims at generating the load current reference taking the state of health into account. Moreover, using a model inversion of an Energetic Macroscopic Representation with time-varying parameters, the coherent references of input flows of gas can be calculated. Finally, the paper details a method to identify and predict the maximum power the fuel cell is able to provide at present time based on a Maximum Power Point Tracking algorithm. Also this algorithm aims at forecasting the Remaining Useful Life for a given power reference. This method is validated on a simulation case. •We develop a time-varying model of PEM fuel cell.•A model inversion method is proposed for references calculation through aging.•An aging tolerant control strategy is detailed based on the state of health.•A Maximal Power Point Tracking strategy robust to aging is proposed.•A RUL forecasting algorithm is developed considering the maximum power.
ISSN:0360-3199
1879-3487
DOI:10.1016/j.ijhydene.2018.11.219