Battery capacity knee-onset identification and early prediction using degradation curvature-Reference-Cited by-同舟云学术

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Battery capacity knee-onset identification and early prediction using degradation curvature

Published:2024-07 Issue: Volume:608 Page:234619
ISSN:0378-7753
Container-title:Journal of Power Sources
language:en
Short-container-title:Journal of Power Sources

Author:

Zhang Huang^ORCID,Altaf Faisal,Wik Torsten

Publisher

Elsevier BV

Reference44 articles.

1. Performance and cost of materials for lithium-based rechargeable automotive batteries;Schmuch;Nature Energy,2018

2. Technical viability of battery second life: A study from the ageing perspective;Martinez-Laserna;IEEE Trans. Ind. Appl.,2018

3. Synthesize battery degradation modes via a diagnostic and prognostic model;Dubarry;J. Power Sources,2012

4. Prognostics of lithium-ion batteries based on Dempster–Shafer theory and the Bayesian Monte Carlo method;He;J. Power Sources,2011

5. Prognostics of Li (NiMnCo) O2-based lithium-ion batteries using a novel battery degradation model;Yang;Microelectron. Reliab.,2017

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