Battery digital twins: Perspectives on the fusion of models, data and artificial intelligence for smart battery management systems-Reference-Cited by-同舟云学术

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Battery digital twins: Perspectives on the fusion of models, data and artificial intelligence for smart battery management systems

Published:2020-08 Issue: Volume:1 Page:100016
ISSN:2666-5468
Container-title:Energy and AI
language:en
Short-container-title:Energy and AI

Author:

Wu Billy^ORCID,Widanage W. Dhammika,Yang Shichun,Liu Xinhua

Publisher

Elsevier BV

Reference69 articles.

1. Degradation diagnostics for lithium ion cells;Birkl;J. Power Sources,2017

2. Lithium-ion battery fast charging: a review;Tomaszewska;ETransportation,2019

3. Review and performance comparison of mechanical-chemical degradation models for lithium-ion batteries;Reniers;J. Electrochem. Soc.,2019

4. Experimental investigation of parametric cell-to-cell variation and correlation based on 1100 commercial lithium-ion cells;Rumpf;J. Energy Storage,2017

5. Cost modeling of lithium-ion battery cells for automotive applications;Patry;Energy Sci. Eng.,2015

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