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题名: Battery Management System for Electric Vehicle and the Study of SOC Estimation
作者: Yuan XQ(袁学庆); Zhao L(赵林); Li B(李博); Liu, Naiming
作者部门: 装备制造技术研究室
会议名称: AASRI International Conference on Industrial Electronics and Applications (IEA)
会议日期: JUN 27-28, 2015
会议地点: London, ENGLAND
会议主办者: Amer Appl Sci Res Inst, Huazhong Normal Univ
会议录: PROCEEDINGS OF THE AASRI INTERNATIONAL CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (IEA 2015)
会议录出版者: ATLANTIS PRESS
会议录出版地: PARIS
出版日期: 2015
页码: 152-156
收录类别: CPCI(ISTP)
ISSN号: 2352-5401
ISBN号: 978-94-62520-65-3
关键词: BMS ; charge equalization ; SOC Estimation
摘要: 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.
语种: 英语
产权排序: 1
WOS记录号: WOS:000359815600038
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/16935
Appears in Collections:装备制造技术研究室_会议论文

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