Estimation of battery SOC based on improved EKF algorithm

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 工业控制网络与系统研究室

	Estimation of battery SOC based on improved EKF algorithm
	Shi G(石刚); Zhao W(赵伟); Han ZH(韩忠华); Liu SS(刘珊珊)
	2016
会议名称	2016 IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2016
会议日期	May 20-22, 2016
会议地点	Chongqing, China
关键词	EKF neural network battery SOC Thevenin circuit Li-ion battery
页码	151-154
通讯作者	石刚
中文摘要	This paper studies the estimation of the state of lithium battery (SOC), and develops an improved extended Kalman filter algorithm for this problem. To compensate deficiencies of the simple polynomial fitting, the neural network algorithm firstly is adopted to simulate the relation curve between the SOC and the parameters of circuit model, which is constructed based on Thevenin circuit. And then the state space equation among the battery's SOC and the voltage of the ends of the RC loop is established, also does the measurement equation which is based on the battery output voltage. In addition, extended Kalman is applied to estimate battery SOC. In the last, the effectiveness of the proposed method is verified using an experimental testing, and the results show that our method can estimate the SOC more accurately comparing with the standard extended Kalman algorithm.
收录类别	EI ; CPCI（ISTP）
产权排序	1
会议主办者	Chongqing Global Union Academy of Science and Technology; Global Union Academy of Science and Technology; IEEE Beijing Section
会议录	Proceedings of 2016 IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2016
会议录出版者	IEEE
会议录出版地	Piscataway, NJ, USA
语种	英语
ISBN号	978-1-4673-9192-4
WOS记录号	WOS:000389505000032
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/19283]
专题	沈阳自动化研究所_工业控制网络与系统研究室
推荐引用方式 GB/T 7714	Shi G,Zhao W,Han ZH,et al. Estimation of battery SOC based on improved EKF algorithm[C]. 见:2016 IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2016. Chongqing, China. May 20-22, 2016.