Battery Management System for Electric Vehicle and the Study of SOC Estimation
- https://doi.org/10.2991/iea-15.2015.38How to use a DOI?
- BMS; charge equalization; SOC Estimation.
The SOC (state of charge) of the Li-ion battery cells in a pack are different because of the property differences, which would lead to over-charging/over-discharging the battery pack and as a result the service life of the battery pack would be reduced. In this article, we designed a battery management system (BMS) for low voltage electric vehicle. The BMS adopted resistance shunt method to avoid over-charging the battery cells. Extended Kalman filter (EKF) was utilized for high precision estimation of SOC, which is very important for remaining the cells working within appropriate SOC and avoiding over-discharging the cells. Experiment result shows that comparing with the commonly used ampere-hour integration approach, EKF decreased estimation error from 15.48% to 7.27%. High precision SOC estimation algorithm and effective charge equalization method can maintain the battery cells working at a good situation and extend the service life of the battery pack, reducing the cost of use indirectly. This is meaningful for Li-ion battery’s industrial application.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yuan Xueqing AU - Zhao Lin AU - Li Bo AU - Liu Naiming PY - 2015/09 DA - 2015/09 TI - Battery Management System for Electric Vehicle and the Study of SOC Estimation BT - Proceedings of the AASRI International Conference on Industrial Electronics and Applications (2015) PB - Atlantis Press SP - 152 EP - 156 SN - 2352-5401 UR - https://doi.org/10.2991/iea-15.2015.38 DO - https://doi.org/10.2991/iea-15.2015.38 ID - Xueqing2015/09 ER -