典型文献
Remaining Useful Life Estimation of Lithium-Ion Battery Based on Gaussian Mixture Ensemble Kalman Filter
文献摘要：
The remaining useful life (RUL) prediction is a crucial indicator for the lithium-ion bat-tery health prognostic. The particle filter (PF), used together with an empirical model, has become one of the most well-accepted techniques for RUL prediction. In this work, a novel filtering algo-rithm, named the Gaussian mixture model (GMM) - ensemble Kalman filter (EnKF) is proposed. It embeds the Gaussian mixture model in the EnKF framework to cope with the non-Gaussian fea-ture of the system state space, and meanwhile address some of the major shortcomings of the PF. The GMM-EnKF and the PF are both applied on public data sets for RUL prediction and the sim-ulation results show superiority of our proposed approach to the PF.
文献关键词：
中图分类号：
作者姓名：
Ruoxia Li;Siyuan Zhang;Peijun Yang
作者机构：
School of Information and Control Engi-neering,Xi'an University of Architecture and Technology,Xi'an 710055,China;School of Mechanical Engineer-ing,Xi'an University of Architecture and Technology,Xi'an 710055,China;Xi'an Boiler&Environmental Pro-tection Engineering Co.,Ltd,Xi'an 710054,China
文献出处：
引用格式：
[1]Ruoxia Li;Siyuan Zhang;Peijun Yang-.Remaining Useful Life Estimation of Lithium-Ion Battery Based on Gaussian Mixture Ensemble Kalman Filter)[J].北京理工大学学报（英文版）,2022(04):340-349
A类：
B类：
Remaining,Useful,Life,Estimation,Lithium,Ion,Battery,Based,Gaussian,Mixture,Ensemble,Kalman,Filter,remaining,useful,life,RUL,prediction,crucial,indicator,lithium,bat,health,prognostic,particle,PF,used,together,empirical,model,has,become,one,most,well,accepted,techniques,In,this,novel,filtering,algo,rithm,named,mixture,GMM,ensemble,EnKF,proposed,It,embeds,framework,cope,fea,system,state,space,meanwhile,address,some,major,shortcomings,are,both,applied,public,data,sets,sim,ulation,results,show,superiority,our,approach
AB值：
0.642199
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