Journal of South China University of Technology(Natural Science Edition) ›› 2012, Vol. 40 ›› Issue (12): 79-85.

• Automotive Engineering • Previous Articles     Next Articles

Parameter Identification and SOC Estimation of Lithium-Ion Battery Pack Used in Electric Vehicles

Luo Yu-tao  Xie Bin  He Xiao-chan   

  1. School of Mechanical and Automotive Engineering∥Guangdong Provincial Key Laboratory of Automotive Engineering,Guangzhou 510640,Guangdong,China
  • Received:2012-05-25 Revised:2012-09-12 Online:2012-12-25 Published:2012-11-02
  • Contact: 罗玉涛(1972-) ,男,博士,教授,主要从事新能源汽车及汽车电子控制等的研究. E-mail:ctytluo@scut.edu
  • About author:罗玉涛(1972-) ,男,博士,教授,主要从事新能源汽车及汽车电子控制等的研究.
  • Supported by:

    国家"863”计划项目( 2012AA110702) ; 教育部新世纪优秀人才支持计划项目( NCET-11-0157)

Abstract:

Proposed in this paper is a SOC ( State of Charge) estimation method to correct the initial error of SOC of the lithium-ion battery pack used in electric vehicles. The new method employs an algorithm combining the extended Kalman filtering with the Ampere-hour integral method. In the investigation,first,the advantages and disadvantages of several equivalent battery circuit models were analyzed,and the improved PNGV model with double RC parallel networks was selected to perform the parameter identification of a lithium-ion battery. Then,a nonlinear dynamic model of the battery in the state-space form was constructed with the help of the improved PNGV model,and the relationship between the open circuit voltage and the corresponding SOC of the battery was analyzed based on the polynomial fitting. Finally,some experiments in the conditions of constant-current pulse discharge and ECE15 were carried out. The results indicate that the proposed algorithm effectively corrects the initial error of SOC and guarantees the estimation accuracy of SOC.

Key words: electric vehicle, lithium-ion battery, state of charge, parameter identification, extended Kalman filtering

CLC Number: