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ORIGINAL RESEARCH article

Front. Energy Res.
Sec. Energy Storage
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1459027

Prediction of Remaining Service Life of Lithium Battery Based on VMD-MC-BiLSTM

Provisionally accepted
Guangxiong Meng Guangxiong Meng 1Zhongnan Liang Zhongnan Liang 2*Zhongyi mou Zhongyi mou 2
  • 1 Shenhua Group (China), Beijing, Beijing Municipality, China
  • 2 Other, Qingdao, China

The final, formatted version of the article will be published soon.

    Abstract：With the popularity of battery-powered products such as electric vehicles and wearable devices, the prediction of remaining life of lithium batteries has become increasingly important. This study proposes a method based on the hybrid neural network for predicting the remaining life of lithium batteries. First, the variational modal decomposition is used for noise reduction processing to maximize the retention of the original information of capacity degradation.Second, the capacity declining trend after noise reduction is modeled and predicted by the combination of bi-directional long-short term memory and monte carlo dropout. Finally, experimental results show that the new method based on the VMD-MC-BiLSTM network achieves good performance in predicting the remaining life of lithium batteries and provides the confidence level, providing new ideas and methods for optimizing lithium battery management systems.

    Keywords: ：Lithium battery, Remaining useful life prediction, VMD-MC-BiLSTM network, deep learning, early diagnosis

    Received: 03 Jul 2024; Accepted: 01 Nov 2024.

    Copyright: © 2024 Meng, Liang and mou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Zhongnan Liang, Other, Qingdao, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.