Extended Kalman Filter for prognostic of Proton Exchange Membrane Fuel Cell
Mathieu Bressel,
Mickael Hilairet,
Daniel Hissel and
Belkacem Ould Bouamama
Applied Energy, 2016, vol. 164, issue C, 220-227
Abstract:
The Proton Exchange Membrane Fuel Cell is a promising energy converter for various fields of application: stationary, portable and mobile. However durability avoids its widespread deployment. Deterioration mechanisms are not all fully understood and that is the reason why the prognostic of such device is gaining attention. This helps determine the present and future state of health of Fuel Cell, to deduce the remaining life in order to take corrective actions. The work presented in this paper attempts to address this issue by proposing a method based on a degradation model. An observer, based on an Extended Kalman Filter, estimates the state of health and the dynamic of the degradations. This result is extrapolated until a threshold is reached and the residual life is deduced. This method allows estimating the lifespan with a single model, robust to uncertainties, whatever the operating conditions are. Simulations are conducted to validate the method. Finally, this framework is used on a set of experimental data from long term test on a 5-cell stack operated under a constant current solicitation.
Keywords: Prognostic; Proton Exchange Membrane Fuel Cell; Extended Kalman Filter (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (47)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261915015214
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:164:y:2016:i:c:p:220-227
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
DOI: 10.1016/j.apenergy.2015.11.071
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().