Electric vehicle state of charge estimation: Nonlinear correlation and fuzzy support vector machine

被引：162

作者：

Sheng, Hanmin ^{[1
]}

Xiao, Jian ^{[1
]}

机构：

[1] Southwest Jiaotong Univ, Sch Elect Engn, Chengdu 610031, Peoples R China

来源：

JOURNAL OF POWER SOURCES | 2015年 / 281卷

基金：

中国国家自然科学基金;

关键词：

Lithium battery; Electric vehicle; State of charge; Nonlinear correlation; Support vector machine; LITHIUM-ION BATTERIES; SVDD;

D O I：

10.1016/j.jpowsour.2015.01.145

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

The aim of this study is to estimate the state of charge (SOC) of the lithium iron phosphate (LiFePO4) battery pack by applying machine learning strategy. To reduce the noise sensitive issue of common machine learning strategies, a kind of SOC estimation method based on fuzzy least square support vector machine is proposed. By applying fuzzy inference and nonlinear correlation measurement, the effects of the samples with low confidence can be reduced. Further, a new approach for determining the error interval of regression results is proposed to avoid the control system malfunction. Tests are carried out on modified COMS electric vehicles, with two battery packs each consists of 24 50 Ah LiFePO4 batteries. The effectiveness of the method is proven by the test and the comparison with other popular methods. Published by Elsevier B.V.

引用

页码：131 / 137

页数：7

共 18 条

[1] Support Vector Machines Used to Estimate the Battery State of Charge [J].

Alvarez Anton, Juan Carlos ;

Garcia Nieto, Paulino Jose ;

Blanco Viejo, Cecilio ;

Vilan Vilan, Jose Antonio .

IEEE TRANSACTIONS ON POWER ELECTRONICS, 2013, 28 (12) :5919-5926

[2] Fuzzy support vector machine based on within-class scatter for classification problems with outliers or noises [J].

An, Wenjuan ;

Liang, Mangui .

NEUROCOMPUTING, 2013, 110 :101-110

[3]

Benkedjouh T., 2012, Prognostics and Health Management (PHM), 2012 IEEE Conference on, P1, DOI [10.1109/ICPHM.2012.6299511, DOI 10.1109/ICPHM.2012.6299511]

[4] Invexity and the Kuhn-Tucker theorem [J].

Hanson, MA .

JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS, 1999, 236 (02) :594-604

[5]

Hecht-Nielsen R., 1989, IJCNN: International Joint Conference on Neural Networks (Cat. No.89CH2765-6), P593, DOI 10.1109/IJCNN.1989.118638

[6] A support vector machine-based state-of-health estimation method for lithium-ion batteries under electric vehicle operation [J].

Klass, Verena ;

Behm, Marten ;

Lindbergh, Goran .

JOURNAL OF POWER SOURCES, 2014, 270 :262-272

[7]

Li Jin, 2008, Journal of System Simulation, V20, P4232

[8]

Lin J, 2007, J SYST ENG ELECTRON, V18, P527, DOI 10.1016/S1004-4132(07)60124-8

[9] SVDD-based outlier detection on uncertain data [J].

Liu, Bo ;

Xiao, Yanshan ;

Cao, Longbing ;

Hao, Zhifeng ;

Deng, Feiqi .

KNOWLEDGE AND INFORMATION SYSTEMS, 2013, 34 (03) :597-618

[10] Electrochemical features of combustion-synthesized lithium cobaltate as cathode material for lithium ion battery [J].

Mamyrbaeva Y.Y. ;

Hobosyan M.A. ;

Kumekov S.E. ;

Martirosyan K.S. .

International Journal of Self-Propagating High-Temperature Synthesis, 2014, 23 (01) :1-8

← 1 2 →