A Review of the Research on Remaining Useful Life Prediction Methods for Lithium-Ion Batteries

Accurate prediction of the Remaining Useful Life (RUL) of Lithium-ion batteries (LiBs) is crucial for the safe and reliable operation of new energy vehicles. This paper analyzes the current research status of the RUL prediction methods of LiBs, summarizes model-based methods, data-driven methods and...

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Bibliographic Details
Published in:	2023 3rd International Conference on Energy, Power and Electrical Engineering (EPEE) pp. 565 - 571
Main Authors:	Feng, Can, Huang, Haoweng, Lu, Guosheng, Zhai, Jianpang, Zhao, Zhigang
Format:	Conference Proceeding
Language:	English
Published:	IEEE 15-09-2023
Subjects:	attention mechanism component Data models data-driven LiBs life prediction Lithium-ion batteries modeling Predictive models Real-time systems RUL Safety Training
Online Access:	Get full text
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Summary:	Accurate prediction of the Remaining Useful Life (RUL) of Lithium-ion batteries (LiBs) is crucial for the safe and reliable operation of new energy vehicles. This paper analyzes the current research status of the RUL prediction methods of LiBs, summarizes model-based methods, data-driven methods and fusion-based methods, comparing their advantages and disadvantages. The key problems of the RUL prediction of LiBs in the current practical application are proposed, and finally the future development trend of the related research is given.
DOI:	10.1109/EPEE59859.2023.10352063