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Application of unscented Kalman filter in the SOC estimation of Li-ion battery for Autonomous Mobile Robot
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
会议录名称2006 IEEE International Conference on Information Acquisition, Vols 1 and 2, Conference Proceedings
出版者IEEE
出版地NEW YORK
2006
页码1279-1283
收录类别EI ; CPCI(ISTP)
EI收录号20082811360705
WOS记录号WOS:000242935800239
产权排序1
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.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/8586
专题机器人学研究室
作者单位1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China
2.Graduate School, Chinese Academy of Sciences, China
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Shi P,Zhao YW. Application of unscented Kalman filter in the SOC estimation of Li-ion battery for Autonomous Mobile Robot[C]//IEEE Robot & Automat Soc, CAS, Inst Intelligent Machines, Chinese Univ Hong Kong, Int Assoc Informat Acquisit, Int Journal Informat Acquisit. NEW YORK:IEEE,2006:1279-1283.
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