电源学报2024，Vol.22Issue(4)：251-259,9.DOI:10.13234/j.issn.2095-2805.2024.4.251
基于VMD和Bat-KELM的仿真变电站蓄电池剩余寿命预测
Remaining Useful Life Prediction of Simulation Substation Batteries Based on VMD and Bat-KELM
摘要
Abstract
Simulation substation batteries often work under discontinuous operation conditions,which will result in capacity regeneration of batteries during their performance degradation.The degradation of batteries shows nonstationary and random characteristics,leading to a low prediction accuracy for the remaining useful life(RUL).Aimed at the problem of RUL prediction of batteries with capacity regeneration,a prediction method is proposed based on variational mode decomposition(VMD)and bat optimized kernel extreme learning machine(Bat-KELM).First,VMD is employed to decompose the battery state-of-health(SOH)time series into overall degradation components and capacity regeneration components.Then,Bat-KELM is used to construct prediction models of each component,so that the prediction accuracy of component trend is improved.At last,the prediction results of all components are blended together to yield the accurate battery SOH prediction results as well as the RUL results.The proposed method is applied to the analysis of battery degradation instance data,and results show its superiority in terms of prediction accuracy compared with the KELM and VMD-KELM models.关键词
仿真变电站/蓄电池/剩余寿命预测/变分模态分解/核极限学习机Key words
Simulation substation/battery/remaining useful life(RUL)prediction/variational mode decomposition(VMD)/kernel extreme learning machine(KELM)分类
信息技术与安全科学引用本文复制引用
任罡,季宁,胡晓丽,李世倩,张洁华,吴祎..基于VMD和Bat-KELM的仿真变电站蓄电池剩余寿命预测[J].电源学报,2024,22(4):251-259,9.基金项目
国网江苏省电力有限公司科技项目(J2021020)This work is supported by Science and Technology Project of State Grid Jiangsu Electric Power Co.,Ltd under the grant J2021020 （J2021020）
