Title :
Estimation of Lithium-ion battery state of charge
Author :
Zhang Di ; Ma Yan ; Bai Qing-Wen
Author_Institution :
State Key Lab. of Automobile Dynamic Simulation, Jilin Univ., Changchun, China
Abstract :
Li-ion batteries have high energy densities and long lifetimes, which are increasingly used in electric vehicles (EV) and hybrid electric vehicles (HEV) now. The state of charge (SOC) is the most important parameter to evaluate the battery and is one of the key factors improving the performance of EV and HEV. With respect to the cells voltage, battery voltage and battery current, the battery model in terms of its circuit representation and mathematical dynamic equations are described. The method estimating the state of charge (SOC) of li-ion batteries based on the extended Kalman filter (EKF) in colored noise is proposed, which predict the SOC of Li-ion battery considers in the discharge working state of battery. The results show that the novel method can increase the accuracy of SOC estimation, eliminate the influence of disturbance.
Keywords :
Kalman filters; battery powered vehicles; hybrid electric vehicles; lithium; secondary cells; EKF; HEV; Li; SOC estimation; battery current; battery model; battery voltage; cell voltage; circuit representation; colored noise; discharge working state; energy densities; extended Kalman filter; hybrid electric vehicles; lithium ion battery; mathematical dynamic equations; state of charge; Batteries; Colored noise; Estimation; Integrated circuit modeling; Kalman filters; Mathematical model; System-on-a-chip; Colored noise; Extended Kalman filter; Li-ion batteries; SOC;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768