期刊文献+

基于数据预处理和计算机VMD-LSTM-GPR的储能系统离子电池剩余寿命预测

Prediction of ion battery remaining life of energy storage system based on data preprocessing and computer VMD-LSTM-GPR
下载PDF
导出
摘要 离子电池剩余寿命影响储能系统运行能力,准确预测电池寿命,有助于判断系统的实时运行状态,为获得较为可靠的预测结果,提出基于数据预处理和计算机VMD-LSTM-GPR的储能系统离子电池剩余寿命预测方法。针对储能系统离子电池剩余寿命预测的相关理论问题进行研究,并联合储能数据预处理标准与计算机VMDLSTM-GPR模型,计算锂离子电池的容量退化能力,从而评估剩余电池寿命,实现基于数据预处理和计算机VMD-LSTM-GPR的储能系统离子电池剩余寿命预测。 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 VMDLSTM-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.
作者 田凌浒 袁炳夏 TIAN Linghu;YUAN Bingxia(CNPC Xinjiang Oilfield Company,Karamay 834000,Xinjiang,China;Huizhou University,Network and Information Center,Huizhou 516007,Guangdong,China)
出处 《储能科学与技术》 CSCD 北大核心 2024年第1期336-338,共3页 Energy Storage Science and Technology
关键词 数据预处理 计算机VMD-LSTM-GPR 储能系统 离子电池 剩余寿命 data preprocessing computer VMD-LSTM-GPR energy storage system ion battery residual life
  • 相关文献

参考文献3

二级参考文献20

共引文献8

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部