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Prediction of mechanical-electrical-thermal behavior in lithium-ion batteries using a neural network surrogate model

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Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Ahead of Print.
Lithium-ion batteries (LIBs) are highly vulnerable to mechanical abuse, which can induce structural damage and internal short circuit (ISC), accompanied by a pronounced temperature rise and increased thermal runaway risk. To enhance predictive safety and ...