Application of machine learning in ultrasonic diagnostics for prismatic lithium-ion battery degradation evaluation

Lithium-ion batteries are essential for electrochemical energy storage, yet they undergo progressive aging during operational lifespan. Consequently, precise estimation of their state of health (SOH) is crucial for effective and safe operation of energy storage systems. This paper investigates the v...

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Autori principali:	Qiying Wang, Da Song, Xingyang Lin, Hanghui Wu, Hang Shen
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Frontiers Media S.A. 2024-03-01
Serie:	Frontiers in Energy Research
Soggetti:	prismatic lithium-ion batteries degradation evaluation predictive performance ultrasonic signal analysis machine learning prediction computational model
Accesso online:	https://www.frontiersin.org/articles/10.3389/fenrg.2024.1379408/full
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