Comparative analysis of two online identification algorithms in a fuel cell system

Kandidayeni, M., Macias, A., Amamou, A. A., Boulon, L. et Kelouwani, S. (2018). Comparative analysis of two online identification algorithms in a fuel cell system. Fuel Cells, 18 (3). pp. 347-358. ISSN 1615-6846 1615-6854 DOI 10.1002/fuce.201800025

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Résumé

Output power of a fuel cell (FC) stack can be controlled through operating parameters (current, temperature, etc.) and is impacted by ageing and degradation. However, designing a complete FC model which includes the whole physical phenomena is very difficult owing to its multivariate nature. Hence, online identification of a FC model, which serves as a basis for global energy management of a fuel cell vehicle (FCV), is considerably important. In this paper, two well-known recursive algorithms are compared for online estimation of a multi-input semi-empirical FC model parameters. In this respect, firstly, a semi-empirical FC model is selected to reach a satisfactory compromise between computational time and physical meaning. Subsequently, the algorithms are explained and implemented to identify the parameters of the model. Finally, experimental results achieved by the algorithms are discussed and their robustness is investigated. The ultimate results of this experimental study indicate that the employed algorithms are highly applicable in coping with the problem of FC output power alteration, due to the uncertainties caused by degradation and operation condition variations, and these results can be utilized for designing a global energy management strategy in a FCV. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Type de document:	Article
Date de dépôt:	21 janv. 2020 21:23
Dernière modification:	21 janv. 2020 21:23
Version du document déposé:	Post-print (version corrigée et acceptée)
URI:	https://depot-e.uqtr.ca/id/eprint/9022

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