Relevance-Based Reconstruction Using an Empirical Mode Decomposition Informer for Lithium-Ion Battery Surface-Temperature Prediction

Accurate monitoring of lithium-ion battery temperature is essential to ensure these batteries’ efficient and safe operation. This paper proposes a relevance-based reconstruction-oriented EMD-Informer machine learning model, which combines empirical mode decomposition (EMD) and the Informer framework...

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Autores principales:	Chao Li, Yigang Kong, Changjiang Wang, Xueliang Wang, Min Wang, Yulong Wang
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2024-10-01
Colección:	Energies
Materias:	lithium-ion batteries informer empirical mode decomposition relevance reconstruction thermal runaway temperature prediction
Acceso en línea:	https://www.mdpi.com/1996-1073/17/19/5001
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