Title :
State-of-Charge estimation for power Li-ion battery pack using Vmin-EKF
Author :
Liu, Xintian ; He, Yao ; Chen, Zonghai
Author_Institution :
Dept. of Autom., Univ. of Sci. & Technol. of China, Hefei, China
Abstract :
An accurate estimation of State-of-Charge (SOC) for power battery pack is very important in the applications of electrical vehicles. Single cell model is not suitable for battery pack of m u Iti cells. Considering the imbalance characteristic of serial connected battery pack, a Vmin model is proposed. The minimal cell load voltage of the battery pack (Vmin) is used as the model measurement variable, and SOC is used as the model state variable. Based on the Vmin state space model, the extended Kaiman filter (EFK) approach is applied to get the recursive estimation of the battery pack´s SOC. Experiments were made to simulate the behaviors of battery pack in the driving conditions. The results showed that accurate and real-time estimation of SOC could be obtained through this approach.
Keywords :
Kalman filters; battery powered vehicles; lithium; secondary cells; SOC estimation; Vmin state space model; Vmin-EKF approach; electrical vehicles; extended Kaiman filter approach; model measurement variable; power lithium ion battery pack; real-time estimation; recursive estimation; serial connected battery pack; state-of-charge estimation; Batteries; State estimation; EKF; Vmin model; power Li-ion battery pack; state-of-charge;
Conference_Titel :
Software Engineering and Data Mining (SEDM), 2010 2nd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-7324-3
Electronic_ISBN :
978-89-88678-22-0