Overview and benchmark analysis of fuel cell parameters estimation for energy management purposes

Kandidayeni, M., Macias, A., Amamou, A. A., Boulon, L., Kelouwani, S. et Chaoui, H. (2018). Overview and benchmark analysis of fuel cell parameters estimation for energy management purposes. Journal of Power Sources, 380 . pp. 92-104. ISSN 0378-7753 DOI 10.1016/j.jpowsour.2018.01.075

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Résumé

Proton exchange membrane fuel cells (PEMFCs) have become the center of attention for energy conversion in many areas such as automotive industry, where they confront a high dynamic behavior resulting in their characteristics variation. In order to ensure appropriate modeling of PEMFCs, accurate parameters estimation is in demand. However, parameter estimation of PEMFC models is highly challenging due to their multivariate, nonlinear, and complex essence. This paper comprehensively reviews PEMFC models parameters estimation methods with a specific view to online identification algorithms, which are considered as the basis of global energy management strategy design, to estimate the linear and nonlinear parameters of a PEMFC model in real time. In this respect, different PEMFC models with different categories and purposes are discussed first. Subsequently, a thorough investigation of PEMFC parameter estimation methods in the literature is conducted in terms of applicability. Three potential algorithms for online applications, Recursive Least Square (RLS), Kalman filter, and extended Kalman filter (EKF), which has escaped the attention in previous works, have been then utilized to identify the parameters of two well-known semi-empirical models in the literature, Squadrito et al. and Amphlett et al. Ultimately, the achieved results and future challenges are discussed. © 2018 Elsevier B.V.

Type de document:	Article
Date de dépôt:	21 janv. 2020 19:11
Dernière modification:	16 mars 2020 04:00
Version du document déposé:	Post-print (version corrigée et acceptée)
URI:	https://depot-e.uqtr.ca/id/eprint/9032

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