State of Charge Estimation of Lithium-Ion Batteries in Electric Drive Vehicles Using Extended Kalman Filtering

被引：378

作者：

Chen, Zheng ^{[1
]}

Fu, Yuhong ^{[1
]}

Mi, Chunting Chris ^{[1
]}

机构：

[1] Univ Michigan, Dept Elect & Comp Engn, Dearborn, MI 48128 USA

来源：

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY | 2013年 / 62卷 / 03期

关键词：

Extended Kalman filter (EKF); hardware-in-the-loop; lithium-ion battery; nonlinear battery model; state of charge (SOC); MANAGEMENT-SYSTEMS; PACKS; HYBRID;

D O I：

10.1109/TVT.2012.2235474

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

080906 [电磁信息功能材料与结构]; 082806 [农业信息与电气工程];

摘要：

In this paper, a more accurate battery state of charge (SOC) estimation method for electric drive vehicles is developed based on a nonlinear battery model and an extended Kalman filter (EKF) supported by experimental data. A nonlinear battery model is constructed by separating the model into a nonlinear open circuit voltage and a two-order resistance-capacitance model. EKF is used to eliminate the measurement and process noise and remove the need of prior knowledge of initial SOC. A hardware-in-the-loop test bench was built to validate the method. The experimental results show that the proposed method can estimate the battery SOC with high accuracy.

引用

页码：1020 / 1030

页数：11

共 19 条

[1]

Development and Validation of a Battery Model Useful for Discharging and Charging Power Control and Lifetime Estimation [J].