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Alternative TitleResearch on prediction of the remaining useful life of lithium-ion batteries based on particle filtering
张凝; 徐皑冬; 王锴; 韩晓佳; Seung Ho Hong
Source Publication高技术通讯
Contribution Rank1
Funding Organization国家自然科学基金( 71651147005) 资助项目。
Keyword锂离子电池 剩余寿命(Rul) 粒子滤波 双指数经验模型
Other AbstractThe particle filtering is used to study the prediction of the remaining useful life ( RUL) of lithium-ion batteries, and a simple and effective algorithm fusing the model method and the data-driven method for RUL predicting is proposed. The algorithm uses the fusion of the model method and the data-driven method to modify the double exponential empirical degradation model to reduce the model parameters and the parameter training difficulty,uses the particle filter algorithm to track the battery capacity degradation process,and uses the auto regression model to modify the observation value of the state space equation to improve the prediction accuracy. The experimental results show that the proposed algorithm can effectively predict the remaining useful life of lithium batteries.
Document Type期刊论文
Corresponding Author张凝
3.Department of Electronic Systems Engineering,Hanyang University
Recommended Citation
GB/T 7714
张凝,徐皑冬,王锴,等. 基于粒子滤波算法的锂离子电池剩余寿命预测方法研究[J]. 高技术通讯,2017,27(8):699-707.
APA 张凝,徐皑冬,王锴,韩晓佳,&Seung Ho Hong.(2017).基于粒子滤波算法的锂离子电池剩余寿命预测方法研究.高技术通讯,27(8),699-707.
MLA 张凝,et al."基于粒子滤波算法的锂离子电池剩余寿命预测方法研究".高技术通讯 27.8(2017):699-707.
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