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基于粒子滤波算法的锂离子电池剩余寿命预测方法研究
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
Department工业控制网络与系统研究室
Source Publication高技术通讯
ISSN1002-0470
2017
Volume27Issue:8Pages:699-707
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
Abstract运用粒子滤波算法,进行了锂离子电池剩余寿命(RUL)的预测,提出了一种基于模型法和数据驱动法相融合的简单有效的RUL预测方法。该方法通过模型法和数据驱动法的融合,将双指数经验退化模型进行变形,以减少模型参数,降低参数训练难度,利用粒子滤波算法跟踪电池容量衰退的过程;为提高预测精确度,引入自回归(AR)时间序列模型修正状态空间方程的观测值。实验证实,该方法可以有效地预估出锂电池的剩余寿命。
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.
Language中文
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/21465
Collection工业控制网络与系统研究室
Corresponding Author张凝
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院大学
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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