State of Charge Estimation of Lithium-ion Batteries Based on An Adaptive Cubature Kalman Filter

被引：0

作者：

Chai, Haoyu ^{[1
]}

Gao, Zhe ^{[2
]}

Jiao, Zhiyuan ^{[1
]}

机构：

[1] Liaoning Univ, Sch Math & Stat, Shenyang, Peoples R China

[2] Liaoning Univ, Coll Light Ind, Shenyang, Peoples R China

来源：

2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC | 2023年

关键词：

State of charge; Lithium-ion battery; Adaptive cubature Kalman filter; Equivalent circuit model; MODEL;

D O I：

10.1109/CCDC58219.2023.10327453

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An adaptive cubature Kalman filter is proposed in this paper to estimate the state of charge (SOC) of a lithium-ion battery. Firstly, a second-order RC equivalent circuit model is constructed to describe the dynamic characteristics of a lithium-ion battery. Secondly, we design a linear Kalman filter and a cubature Kalman filter to achieve the adaptive estimation of SOC, model parameters and the coefficients in the measurement equation. Thirdly, the noise covariance matrices are adaptively adjusted in order to further improve the estimation accuracy of the proposed algorithm. Finally, the estimation accuracy and adaptability of the algorithm proposed in this paper are verified by different experiments.

引用

页码：5244 / 5249

页数：6

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