Early prediction of remaining useful life for lithium-ion batteries based on CEEMDAN-transformer-DNN hybrid model

Early prediction of remaining useful life for lithium-ion batteries based on CEEMDAN-transformer-DNN hybrid model

A reliable and safe energy storage system utilizing lithium-ion batteries relies on the early prediction of remaining useful life (RUL). Despite this, accurate capacity prediction can be challenging if little historical capacity data is available due to the capacity regeneration and the complexity o...

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Bibliographic Details
Main Authors: Yuxiang Cai, Weimin Li, Taimoor Zahid, Chunhua Zheng, Qingguang Zhang, Kun Xu
Format: Article
Language:English
Published: Elsevier 2023-07-01
Series:Heliyon
Subjects:
Early prediction
RUL
Lithium-ion batteries
Capacity regeneration
CEEMDAN
Transformer
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844023049629

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http://www.sciencedirect.com/science/article/pii/S2405844023049629

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