Advancing battery safety: Integrating multiphysics and machine learning for thermal runaway prediction in lithium-ion battery module-Reference-Cited by-同舟云学术

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Advancing battery safety: Integrating multiphysics and machine learning for thermal runaway prediction in lithium-ion battery module

Published:2024-09 Issue: Volume:614 Page:235015
ISSN:0378-7753
Container-title:Journal of Power Sources
language:en
Short-container-title:Journal of Power Sources

Author:

Das Goswami Basab Ranjan,Abdisobbouhi Yasaman,Du Hui,Mashayek Farzad^ORCID,Kingston Todd A.^ORCID,Yurkiv Vitaliy^ORCID

Publisher

Elsevier BV

Reference55 articles.

1. Safety focused modeling of lithium-ion batteries: a review;Abada;J. Power Sources,2016

2. Unraveling ion diffusion pathways and energetics in polycrystalline SEI of lithium-based batteries: combined cryo-HRTEM and DFT study;Das Goswami;J. Phys. Chem. C,2023

3. Electric vehicle revolution and implications: ion battery and energy;Qiu;Eng. Sci.,2022

4. Thermal model of cylindrical and prismatic lithium-ion cells;Hatchard;J. Electrochem. Soc.,2001

5. A three-dimensional thermal abuse model for lithium-ion cells;Kim;J. Power Sources,2007

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