Title :
State-of-charge estimation for a single Lithium battery cell using Extended Kalman Filter
Author :
Hussein, Ala Al-Haj ; Batarseh, Issa
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
Abstract :
An accurate state-of-charge (SOC) estimation is desired in most battery systems. It increases the reliability of the system and extends the lifetime of the battery. This paper proposes an Extended Kalman Filter (EKF) algorithm to estimate the SOC of a Lithium battery cell. To implement the SOC algorithm, an improved Lithium battery cell model is used. The results of the model and EKF algorithm show the effectiveness and ease of implementation of the proposed technique.
Keywords :
Kalman filters; lithium; nonlinear filters; power filters; secondary cells; Li; extended Kalman filter algorithm; single battery cell; state-of-charge estimation; Batteries; Estimation; Hysteresis; Integrated circuit modeling; Kalman filters; Mathematical model; System-on-a-chip; Extended Kalman Filter (EKF); State-of-charge (SOC); hysteresis voltage; relaxation;
Conference_Titel :
Power and Energy Society General Meeting, 2011 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4577-1000-1
Electronic_ISBN :
1944-9925
DOI :
10.1109/PES.2011.6039679
