Journal of South China University of Technology(Natural Science) >

2020 , Vol. 48 >Issue 2: 69 - 75

DOI: https://doi.org/10.12141/j.issn.1000-565X.180562

Traffic & Transportation Engineering

SOC Estimation of Li-Ion Power Battery Based on STEKF

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  • 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
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。

Received date: 2018-11-13

  Revised date: 2019-09-04

  Online published: 2020-02-01

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

Cite this article

TIAN Sheng Lü Qing LI Yafei . SOC Estimation of Li-Ion Power Battery Based on STEKF[J]. Journal of South China University of Technology(Natural Science), 2020 , 48(2) : 69 -75 . DOI: 10.12141/j.issn.1000-565X.180562

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