State of health estimation for lithium‐ion batteries using modern heuristic algorithm optimized multiple kernel extreme learning

Abstract Accurate state of health (SOH) estimation is crucial for the safe operation of lithium‐ion batteries. To address the limited capability of traditional models in characterizing nonlinear degradation, this study proposes a novel data‐driven SOH estimation framework. First, an indirect health...

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Auteurs principaux:	Yumin Zhang, Yongtao Liu, Pingfeng Ye, Xingquan Ji, Yunqi Wang, Kezhuang Xue, Xuchen Ma
Format:	Artigo
Langue:	Inglês
Publié:	Wiley 2026-06-01
Collection:	Energy Conversion and Economics
Sujets:	data‐driven gold rush‐inspired grey wolf optimizer hybrid multiple kernel extreme learning machine state of health
Accès en ligne:	https://doi.org/10.1049/enc2.70041
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