Electrochemical–mechanical coupled model for computationally efficient prediction of long-term capacity fade of lithium-ion batteries-Reference-Cited by-同舟云学术

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Electrochemical–mechanical coupled model for computationally efficient prediction of long-term capacity fade of lithium-ion batteries

Published:2024-05 Issue: Volume:86 Page:111224
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Kim Kwangrae,Lee Gyeonghwan,Chun Huiyong^ORCID,Baek Jongchan^ORCID,Pyeon Hyeonjang^ORCID,Kim Minho,Han Soohee^ORCID

Publisher

Elsevier BV

Reference39 articles.

1. A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations;Hannan;Renew. Sustain. Energy Rev.,2017

2. Estimation of transportation battery second life for use in electricity grid systems;Strickland;IEEE Trans. Sustain. Energy,2014

3. Primary and secondary use of electric mobility batteries from a life cycle perspective;Faria;J. Power Sources,2014

4. Identification and machine learning prediction of knee-point and knee-onset in capacity degradation curves of lithium-ion cells;Fermín-Cueto;Energy AI,2020

5. Development of first principles capacity fade model for Li-ion cells;Ramadass;J. Electrochem. Soc.,2004

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