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Online prediction of lithium-ion battery’s remaining useful life with multiple health indicators and hybrid SAE-LSTM-1DCNN model

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Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, Ahead of Print.
Accurate and efficient prediction of the remaining useful life (RUL) of lithium-ion batteries is critical for ensuring their safe operation, preventing catastrophic accidents, and mitigating potential economic losses. Health indicators (HIs) are capable ...