Journal of South China University of Technology (Natural Science Edition) ›› 2020, Vol. 48 ›› Issue (2): 69-75.doi: 10.12141/j.issn.1000-565X.180562

• Traffic & Transportation Engineering • Previous Articles     Next Articles

SOC Estimation of Li-Ion Power Battery Based on STEKF

TIAN Sheng1 Lü Qing1 LI Yafei2#br#   

  1. 1． School of Civil Engineering and Transportation，South China University of Technology，Guangzhou 510640，Guangdong，China; 2． Guangzhou Automobile Group Co．，Ltd．，Guangzhou 511434，Guangdong，China
  • Received:2018-11-13 Revised:2019-09-04 Online:2020-02-25 Published:2020-02-01
  • Contact: 田晟(1969-)，男，博士，副教授，硕士生导师，主要从事新能源汽车与动力电池技术研究。 E-mail:shitian1@scut.edu.cn
  • About author:田晟(1969-)，男，博士，副教授，硕士生导师，主要从事新能源汽车与动力电池技术研究。
  • Supported by:
    Supported by the China Scholarship Council Program ( 201706155003) and the Science and Technology Plan- ning Project of Guangdong Province ( 2015A080803001)

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Abstract: A method based on strong tracking extended Kalman filter ( STEKF) with multiple suboptimal fading factors was proposed to accurately estimate the state of charge ( SOC) of EV power batteries online． Taking a lithi- um-ion battery as the research object，the second-order ＲC equivalent circuit model of a lithium-ion battery was es- tablished based on its external characteristics and related mechanism． Then the least square method was used to identify the model parameters，and the STEKF nonlinear state space equation of the battery was established accor- ding to the equivalent circuit model． Finally，the simulation was carried out under ECE15 condition． The results show that the error of STEKF in estimating battery SOC is kept within 2% ，so this method can estimate battery SOC accurately．

Key words: lithium-ion battery, state of charge, equivalent circuit model, strong tracking extended Kalman fil- ter