电源技术2018，Vol.42Issue(4)：568-571,4.
基于多种模型的扩展卡尔曼滤波算法的SOC估算
Estimation of battery SOC based on extended Kalman filter algorithm of multiple models
贾亮 1王真真 2孙延鹏 2孙伟1
作者信息
- 1. 沈阳航空航天大学辽宁省通用航空重点实验室,辽宁沈阳110136
- 2. 沈阳航空航天大学电子信息工程学院,辽宁沈阳110136
- 折叠
摘要
Abstract
In order to improve the accuracy of estimation of battery state of charge (SOC),the influence of the two cell models in SOC estimation was compared.Two battery models were established:first order simplified model and two-order RC model.The extended Kalman filter estimation method was used to estimate through the two models respectively.The experimental conditions were simulated by Matlab.The research results show that the first order simplified model is relatively poor,and the error is more than 10％,but the estimation accuracy of second-order RC model is higher with error of only 5％ and the estimation matrix can be implemented in hardware,providing a precise estimation scheme for the battery management system.关键词
荷电状态/扩展卡尔曼滤波算法/电池模型/电池管理Key words
state of charge/extended Kalman filter algorithm/battery model/battery management分类
信息技术与安全科学引用本文复制引用
贾亮,王真真,孙延鹏,孙伟..基于多种模型的扩展卡尔曼滤波算法的SOC估算[J].电源技术,2018,42(4):568-571,4.
