Proton Exchange Membrane Fuel Cell Prognosis Based on Frequency-Domain Kalman Filter
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Titre | Proton Exchange Membrane Fuel Cell Prognosis Based on Frequency-Domain Kalman Filter |
Type de publication | Journal Article |
Year of Publication | 2021 |
Auteurs | Ao Y, Laghrouche S, Depernet D, Chen K |
Journal | IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION |
Volume | 7 |
Pagination | 2332-2343 |
Date Published | DEC |
Type of Article | Article |
ISSN | 2332-7782 |
Mots-clés | Computational modeling, Data models, degradation, Degradation prognosis, frequency-domain Kalman filter (FDKF), Fuel Cells, Load modeling, Model-driven method, Predictive models, Prognostics and health Management, Proton exchange membrane fuel cell (PEMFC), voltage degradation model |
Résumé | The degradation seriously affects the durability and cost of the proton exchange membrane fuel cell (PEMFC). This article presents a novel model-driven method based on the frequency-domain Kalman filter (FDKF) and voltage degradation model to predict the degradation of PEMFC in the frequency domain. The advantage of the proposed FDKF method is that it can process the data in groups; thus, the computation time can be greatly reduced with high accuracy. Two degradation experiments under constant and quasi-dynamic currents have been used to demonstrate its prognosis performances under different conditions and different training times. Compared with the traditional time-domain extended Kalman filter method and literature, it has been demonstrated that the proposed one has higher accuracy and requires much less calculation time. |
DOI | 10.1109/TTE.2021.3077506 |