SOC Estimation of Lithium Battery Based on Fuzzy Kalman Filter Algorithm

被引：0

作者：

Ma, Chuang ^{[1
]}

Wu, Qinghui ^{[1
]}

Hou, Yuanxiang ^{[1
]}

Cai, Jianzhe ^{[1
]}

机构：

[1] Bohai Univ, Coll Engn, Jinzhou, Liaoning, Peoples R China

来源：

2020 35TH YOUTH ACADEMIC ANNUAL CONFERENCE OF CHINESE ASSOCIATION OF AUTOMATION (YAC) | 2020年

关键词：

SOC; Lithium battery; Kahrcan filter algorithm and fitzzy control;

D O I：

10.1109/YAC51587.2020.9337670

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Aiming at predicting problem for the charged state of lithium batteries in electric vehicles(EV), an algorithm derived from fuzzy extended kalman filter is proposed on the basis of large estimation deviation of traditional methods. A second-order RC equivalent circuit model combining Thevenin and RC network is established to recognize the parameters for the battery model.A fuzzy controller is added into the traditional kalman filter algorithm to evaluate the state of charge (SOC) for battery from this paper. Using Matlab to verify, as well as the simulation results indicate the improved way enhances the accuracy of the estimated SOC.

引用

页码：324 / 329

页数：6