RUL prediction of lithium ion battery based on CEEMDAN-CNN BiLSTM model
With the wide application of lithium ion batteries, the importance of life prediction is also highlighted. The prediction of the remaining life of lithium ion battery is an important part of its health management, and accurate prediction can improve the safety of equipment. In this paper, a method f...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2023-10-01
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Series: | Energy Reports |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484723008648 |