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Hybrid gray wolf optimization method in support vector regression framework for highly precise prediction of remaining useful life of lithium-ion batteries

Crossref DOI link: https://doi.org/10.1007/s11581-023-05072-1

Published Online: 2023-06-06

Published Print: 2023-09

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Zhang, Mengyun

Wang, Shunli

Xie, Yanxin

Yang, Xiao

Hao, Xueyi

Fernandez, Carlos
Funding

Funding for this research was provided by:

National Natural Science Foundation of China projects (61801407)

Scientific Research Project of Sichuan Provincial Department of Education (17ZB0453)

Natural Science Foundation of Sichuan Province (2023NSFSC1436)
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Text and Data Mining valid from 2023-06-06

Version of Record valid from 2023-06-06
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Article History

Received: 19 April 2023

Revised: 26 May 2023

Accepted: 30 May 2023

First Online: 6 June 2023

Declarations

:

: This study does not involve human and/or animal studies.

: The authors declare that they have no known competing financial interests.

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