Online State-of-Charge and State-of-Health Estimation of Lithium Battery Based on Equivalent Circuit Model

被引：0

作者：

Kung, Chung-Chun ^{[1
]}

Chang, Shuo-Chieh ^{[1
]}

Chen, Ti-Hung ^{[2
]}

机构：

[1] Tatung Univ, Dept Elect Engn, Taipei, Taiwan

[2] Lunghwa Univ Sci & Technol, Dept Comp Informat & Network Engn, Taoyuan, Taiwan

来源：

NEW TRENDS ON SYSTEM SCIENCES AND ENGINEERING | 2015年 / 276卷

关键词：

Lithium battery; state-of-charge; state-of-health; fuzzy c-regression model; C-REGRESSION MODEL; FADING MECHANISM; ION BATTERY; CAPACITY;

D O I：

10.3233/978-1-61499-522-7-433

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a method for the estimation of the state-of-charge (SOC) and state-of-health (SOH) of lithium battery based on the equivalent circuit model (ECM). We apply the fuzzy c-regression model (FCRM) to express each of the parameters in the ECM. Based on these FCRMs and ECM, a state estimator is proposed to estimate SOC of the battery. A SOH model accompanied with the state estimator is established to estimate the SOH based on the charging data of lithium battery. Simulation results show that the proposed method is suitable and realizable for the lithium battery.

引用

页码：433 / 446

页数：14

共 19 条

[1]

[Anonymous], 2010, Battery Management Systems for Large Lithium Ion Battery Packs

[2] A novel approach for state of charge estimation based on adaptive switching gain sliding mode observer in electric vehicles [J].