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Remaining useful life prediction of lithium-ion batteries based on performance degradation mechanism analysis and improved Deep Extreme Learning Machine model

Crossref DOI link: https://doi.org/10.1007/s11581-024-05685-0

Published Online: 2024-07-06

Published Print: 2024-09

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

Authors

Feng, Renjun

Wang, Shunli

Yu, Chunmei

Fernandez, Carlos
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (62173281)

Sichuan Science and Technology Program (23ZDYF0734)

Dazhou City School Cooperation Project (DZXQHZ006)

Technopole Talent Summit Project (KJCRCFH08)
License Information

Text and Data Mining valid from 2024-07-06

Version of Record valid from 2024-07-06
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Article History

Received: 30 May 2024

Revised: 21 June 2024

Accepted: 30 June 2024

First Online: 6 July 2024

Declarations

:

: This paper does not contain any studies involving humans or animals.

: The authors declare no competing interests.

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