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题名: Application of unscented Kalman filter in the SOC estimation of Li-ion battery for Autonomous Mobile Robot
作者: Shi P(石璞) ; Zhao YW(赵忆文)
作者部门: 机器人学研究室
会议名称: IEEE International Conference on Information Acquisition
会议日期: August 20-23, 2006
会议地点: Weihai, China
会议主办者: IEEE Robot & Automat Soc, CAS, Inst Intelligent Machines, Chinese Univ Hong Kong, Int Assoc Informat Acquisit, Int Journal Informat Acquisit
会议录: 2006 IEEE International Conference on Information Acquisition, Vols 1 and 2, Conference Proceedings
会议录出版者: IEEE
会议录出版地: NEW YORK
出版日期: 2006
页码: 1279-1283
收录类别: CPCI(ISTP) ; EI
ISBN号: 1-4244-0528-9
关键词: UKF ; Li-ion battery ; SOC ; EKF ; AMR
摘要: When the Autonomous Mobile Robot(AMR) is popular in unknown environment, accurate estimation of SOC(State of Charge) is becoming one of the primary challenges in Autonomous Mobile Robots research. However, as defects of the Extended Kalman Filter(EKF) in nonlinear estimation, there exists estimated error. which affects the estimation accuracy, when it is adopted in nonlinear estimation of a battery system. In order to vield the higher accuracy of SOC estimation, a novel method-Unscented Kalman Filter (UKF) was employed in SOC estimation for a battery system. The EKF and UKF are compared through experiments. Experimental results show that the UKF is superior to the EKF in battery SOC estimation for AMR.
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8586
Appears in Collections:机器人学研究室_会议论文

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