Remaining useful life prediction of Lithium-ion batteries based on data preprocessing and CNN-LSSVR algorithm

Lithium-ion batteries are now widely available in power and energy systems. Targeting the thorny issues of limited battery historical cycle data and the impact of uncertainty in the data collection process in practical applications, this study proposes a Remaining useful life (RUL) prediction method...

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Autors principals:	Ti Dong, Yiming Sun, Jia Liu, Qiang Gao, Chunrong Zhao, Wenjiong Cao
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2025-06-01
Col·lecció:	International Journal of Electrical Power & Energy Systems
Matèries:	Lithium-ion batteries RUL prediction Data preprocessing Multi-resolution singular value decomposition (MRSVD) Convolutional neural network-least squares support vector regression (CNN-LSSVR)
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S014206152500170X
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