Prediction of the Remaining Useful Life of Lithium–Ion Batteries Based on Mode Decomposition and ED-LSTM

Prediction of the Remaining Useful Life of Lithium–Ion Batteries Based on Mode Decomposition and ED-LSTM

The prediction of remaining useful life (RUL) of lithium–ion batteries is key to the reliability assessment of batteries and affects safe application of batteries. This article introduces a CEEMDAN-RF-MHA-ED-LSTM method. Using CEEMDAN, the battery capacity data were decomposed to obtain intrinsic mo...

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Bibliographic Details
Main Authors: Bingzeng Song, Guangzhao Yue, Dong Guo, Hanming Wu, Yonghai Sun, Yuhua Li, Bin Zhou
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Batteries
Subjects:
lithium–ion battery
life prediction
modal decomposition
particle swarm optimization algorithm
long short-term memory network
Online Access:https://www.mdpi.com/2313-0105/11/3/86
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