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Article Dans Une Revue eTransportation Année : 2023

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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Dates et versions

hal-04224232 , version 1 (01-10-2023)

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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