Title :
Kalman filter based state-of-charge estimation for lithium-ion batteries in hybrid electric vehicles using pulse charging
Author :
Yatsui, Mori W. ; Bai, Hua
Author_Institution :
Dept. of Electr. & Comput. Eng., Kettering Univ., Flint, MI, USA
Abstract :
The battery is one of the most important energy storage components in EV/HEV. Failing to estimate the state of the charge accurately will bring the risk of overcharge or over discharge. The traditional Coulomb counting method will bring accumulated error over time, therefore high deviation occurs between the estimated and real state of charge. Different estimation strategies are compared in this paper, i.e., Coulomb counting method, open-circuit-voltage method and Kalman filter based state of charge estimation. Experimental results validate the effectiveness of Kalman filter during the on-line application.
Keywords :
Kalman filters; battery powered vehicles; hybrid electric vehicles; secondary cells; Coulomb counting method; EV-HEV; Kalman filter; energy storage components; hybrid electric vehicles; lithium-ion batteries; open-circuit-voltage method; pulse charging; state-of-charge estimation; Batteries; Battery charge measurement; Estimation; Kalman filters; Mathematical model; Resistance; System-on-a-chip; Coulomb Counting Method; Kalman Filter; Lithium-ion Battery; Open-circuit-voltage Method; Plug-in Hybrid Electric Vehicle; State of Charge;
Conference_Titel :
Vehicle Power and Propulsion Conference (VPPC), 2011 IEEE
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-61284-248-6
Electronic_ISBN :
Pending
DOI :
10.1109/VPPC.2011.6042988