Estimation of battery SOC based on improved EKF algorithm
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 batterys 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.
EKF neural network battery SOC Thevenin circuit Li-ion battery
Shi Gang Zhao Wei Han Zhonghua Liu Shanshan
Laboratory of Industrial Control Network and System Shenyang Institute of Automation Shenyang,China Faculty of Information and Control Engineering Shen yang Jian zhu University Shenyang,China
国际会议
重庆
英文
151-154
2016-03-20（万方平台首次上网日期，不代表论文的发表时间）