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题名: A Battery State of Charge Estimation Method with Extended Kalman Filter
作者: Zhang F(张飞) ; Liu GJ(刘光军) ; Fang LJ(房立金)
作者部门: 机器人学研究室
会议名称: IEEE/ASME International Conference on Advanced Intelligent Mechatronics
会议日期: July 2-5, 2008
会议地点: XIan, China
会议主办者: IEEE
会议录: 2008 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS, VOLS 1-3
会议录出版者: IEEE
会议录出版地: NEW YORK
出版日期: 2008
页码: 1008-1013
收录类别: CPCI(ISTP) ; EI
ISBN号: 978-1-4244-2494-8
关键词: Battery ; state of charge ; extended Kalman filter ; state estimation
摘要: In this paper, a battery State of Charge (SOC) estimation method based on the extended Kalman filter is proposed. In some known battery SOC estimation methods, it is assumed that the relationship between battery open circuit voltage and SOC is linear and static. However, this relationship is only piecewisely linear in practice and varies with the ambient temperature, as assumed in this work. The proposed model assumption matches better with the real battery behavior. A battery is modeled as a nonlinear system, with the SOC defined as a system state. The extended Kalman filter is applied to estimate SOC directly for a lithium battery pack. The effectiveness of the proposed method is verified on a power transmission line inspection robot. The experimental results verify the effectiveness of the proposed method.
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8465
Appears in Collections:机器人学研究室_会议论文

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