Energy Storage Science and Technology ›› 2024, Vol. 13 ›› Issue (1): 336-338.doi: 10.19799/j.cnki.2095-4239.2023.0920

• Energy Storage System and Engineering • Previous Articles     Next Articles

Prediction of ion battery remaining life of energy storage system based on data preprocessing and computer VMD-LSTM-GPR

Linghu TIAN1(), Bingxia YUAN2()   

  1. 1.CNPC Xinjiang Oilfield Company, Karamay 834000, Xinjiang, China
    2.Huizhou University, Network and Information Center, Huizhou 516007, Guangdong, China
  • Received:2023-12-19 Revised:2023-12-28 Online:2024-01-05 Published:2024-01-22
  • Contact: Bingxia YUAN E-mail:tianlh@petrochina.com.cn;13928319050@139.com

Abstract:

The remaining life of ion battery affects the operation ability of energy storage system, and accurate prediction of battery life is helpful to judge the real-time operation state of the system. In order to obtain reliable prediction results, a prediction method of ion battery remaining life of energy storage system based on data preprocessing and computer VMD-LSTM-GPR is proposed. Research on the related introduction to the remaining life prediction of ion batteries in the energy storage system, and combine the energy storage data preprocessing standard with the computer VMD-LSTM-GPR model to calculate the capacity degradation capability of lithium-ion batteries, so as to evaluate the remaining battery life. The remaining life prediction of ion battery of energy storage system based on data preprocessing and computer VMD-LSTM-GPR was realized.

Key words: data preprocessing, computer VMD-LSTM-GPR, energy storage system, ion battery, residual life

CLC Number: