Machine learning enables rapid state of health estimation of each cell within battery pack

Yu, Quanqing; Nie, Yuwei; Guo, Shanshan; Li, Junfu; Zhang, Chengming

doi:10.1016/j.apenergy.2024.124165

Applied Energy

2024

DOI: 10.1016/j.apenergy.2024.124165

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Machine learning enables rapid state of health estimation of each cell within battery pack

Quanqing Yu,

Yuwei Nie,

Shanshan Guo

et al.

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Cited by 4 publications

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Machine learning enables rapid state of health estimation of each cell within battery pack

Cited by 4 publications

References 39 publications

Coupling effect of state of charge and loading rate on internal short circuit of lithium-ion batteries induced by mechanical abuse

Coupling effect of state of charge and loading rate on internal short circuit of lithium-ion batteries induced by mechanical abuse

Enhancing data-driven-based state of health estimation for diverse battery applications through effective feature construction

A comparative study on mechanical-electrical-thermal characteristics and failure mechanism of LFP/NMC/LTO batteries under mechanical abuse

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