| Issue |
E3S Web Conf.
Volume 118, 2019
2019 4th International Conference on Advances in Energy and Environment Research (ICAEER 2019)
|
|
|---|---|---|
| Article Number | 02025 | |
| Number of page(s) | 4 | |
| Section | Energy Equipment and Application | |
| DOI | https://doi.org/10.1051/e3sconf/201911802025 | |
| Published online | 04 October 2019 | |
Online Estimation of Li-ion Battery SOC for Electric Vehicles Based on An Improved AEKF
State Grid Energy Research Institute Co.LTD Beijing China
* Corresponding author: fengkhui@163.com
The purpose of this paper is to discuss how to eliminate the influence of noise time -varying characteristics on the accuracy of SOC estimation. Based on the matlab/simulink platform, the Thevenin equivalent circuit model of the battery is built, and an improved Adaptive Extend Kalman Filter (AEKF) is designed, which is compared with the Extend Kalman filter algorithm (EKF).The simulation results are shown that the improved AEKF algorithm results in effective online estimation SOC and the estimation accuracy is higher than the EKF algorithm.
© The Authors, published by EDP Sciences, 2019
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