An ensemble model for predicting the remaining useful performance of lithium-ion batteries

被引:710
作者
Xing, Yinjiao [1 ,2 ]
Ma, Eden W. M. [1 ]
Tsui, Kwok-Leung [1 ,2 ]
Pecht, Michael [3 ]
机构
[1] City Univ Hong Kong, Ctr Prognost & Syst Hlth Management, Kowloon, Hong Kong, Peoples R China
[2] City Univ Hong Kong, Dept Syst Engn & Engn Management, Kowloon, Hong Kong, Peoples R China
[3] Univ Maryland, CALCE, College Pk, MD 20740 USA
基金
美国国家科学基金会;
关键词
MANAGEMENT-SYSTEMS; CAPACITY FADE; HEALTH; STATE; PROGNOSTICS; REGRESSION;
D O I
10.1016/j.microrel.2012.12.003
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
080906 [电磁信息功能材料与结构]; 082806 [农业信息与电气工程];
摘要
We developed an ensemble model to characterize the capacity degradation and predict the remaining useful performance (RUP) of lithium-ion batteries. Our model fuses an empirical exponential and a polynomial regression model to track the battery's degradation trend over its cycle life based on experimental data analysis. Model parameters are adjusted online using a particle filtering (PF) approach. Experiments were conducted to compare our ensemble model's prediction performance with the individual results of the exponential and polynomial models. A validation set of experimental battery capacity data was used to evaluate our model. In our conclusion, we presented the limitations of our model. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:811 / 820
页数:10
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