High-precision and efficiency diagnosis for polymer electrolyte membrane fuel cell based on physical mechanism and deep learning
Résumé
As a nonlinear and dynamic system, the polymer electrolyte membrane
fuel cell (PEMFC) system requires a comprehensive failure
prediction and health management system to ensure its safety and
reliability. In this study, a data-driven PEMFC health diagnosis
framework is proposed, coupling the fault embedding model, sensor
pre-selection method and
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https://hal.science/hal-04224232
Soumis le : dimanche 1 octobre 2023-20:40:09
Dernière modification le : lundi 2 octobre 2023-03:22:34
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Identifiants
- HAL Id : hal-04224232 , version 1
Citer
Zhichao Gong, Bowen Wang, Yanqiu Xing, Yifan Xu, Zhengguo Qin, et al.. High-precision and efficiency diagnosis for polymer electrolyte membrane fuel cell based on physical mechanism and deep learning. eTransportation, 2023, 18, pp.100275 (14). ⟨hal-04224232⟩
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