| Title |
A Study on Battery SOC Estimation Based on Extended Kalman Filter Reflecting Battery Impedance Change |
| Authors |
Jae-Hyung Lee ; Gyeong-Hwan Kim ; Jae-Jung Yun |
| DOI |
http://doi.org/10.5207/JIEIE.2021.35.1.028 |
| Keywords |
Battery Model; Battery Management System(BMS); Extended Kalman Filter(EKF); State of Charge(SOC) |
| Abstract |
The state of charge(SOC) of battery should be accurately estimated because it is used as basic data for various functions of the battery management(BMS) as well as the remaining battery capacity. Extended Kalman Filter(EKF) based on a battery model is widely used as a real-time SOC estimation technique. However, the parameters of battery model are slightly different for each SOC section and changed by C-rate. As a result, if the battery parameters are used a fixed value, the accuracy of SOC estimation using EKF is decreased. In this paper, to improve the accuracy of the SOC estimation using EKF, the changes in battery parameters according to C-rate were analyzed for five SOC sections. Also, the accuracy of the SOC estimation according to the number of SOC sections was calculated by simulation. Experimental results show that the battery parameters reduce as C-rate increases. In addition, as the SOC decreased, the internal resistor Ri and loss resistor Rd increased, but the double layer capacitor Cd decreased. Therefore, in order to increase the accuracy of SOC estimation using EKF, it is necessary to reflect the changes in battery parameters in each SOC section according to the C-rage. This was verified by simulation. |