文献详情
Similarity recognition of online data curves based on dynamic spatial time warping for the estimation of lithium-ion battery capacity
文献类型期刊
作者Tao, Laifa[1];Lu, Chen[2];Noktehdan, Azadeh[3]
机构
通讯作者Lu, C (reprint author), Beihang Univ, Sch Reliabil & Syst Engn, Beijing 100191, Peoples R China.
来源信息年:2015  卷:293  页码范围:751-759  
期刊信息JOURNAL OF POWER SOURCES影响因子和分区  ISSN:0378-7753
关键词Dynamic spatial time warping; Lithium-ion battery; Capacity estimation; Similarity recognition; Online data curves
增刊正刊
摘要Battery capacity estimation is a significant recent challenge given the complex physical and chemical processes that occur within batteries and the restrictions on the accessibility of capacity degradation data. In this study, we describe an approach called dynamic spatial time warping, which is used to determine the similarities of two arbitrary curves. Unlike classical dynamic time warping methods, this approach can maintain the invariance of curve similarity to the rotations and translations of curves, which is vital in curve similarity search. Moreover, it utilizes the online charging or discharging data that are easily collected and do not require special assumptions. The accuracy of this approach is verified using NASA battery datasets. Results suggest that the proposed approach provides a highly accurate means of estimating battery capacity at less time cost than traditional dynamic time warping methods do for different individuals and under various operating conditions. (C) 2015 Elsevier B.V. All rights reserved.
收录情况SCIE(WOS:000358809700089)  EI(20152400932587)  
所属部门可靠性与系统工程学院
DOI10.1016/j.jpowsour.2015.05.120
学科电化学;能源与燃料
百度学术Similarity recognition of online data curves based on dynamic spatial time warping for the estimation of lithium-ion battery capacity
语言外文
被引频次3
人气指数38
浏览次数38
基金Fundamental Research Funds for the Central Universities [YWF-14-KKX-015]; National Natural Science Foundation of China [61074083]; Technology Foundation Program of National Defense [Z132013B002]
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