Title :
A Practical and Accurate SOC Estimation System for Lithium-Ion Batteries by EKF
Author :
Lin, L. ; Kawarabayashi, N. ; Fukui, M. ; Tsukiyama, S. ; Shirakawa, I.
Author_Institution :
Grad. Sch. of Sci. & Eng. Adv. Electr., Electron. & Comput. Syst., Ritsumeikan Univ. Kusatsu, Kusatsu, Japan
Abstract :
In this paper, we propose a practical and accurate SOC (State of Charge) estimation system for Lithium- ion battery. The algorithm of SOC estimation uses the Extended Kalman filter, and estimates the SOC using OCV-SOC Curve, internal impedance, and the external current and voltage of a battery.12288; It is constructed on a discrete-time system model of battery model using numerical analysis method, and employs a SOC-OCV curve using simple polynomial function. Also, it provides a noise tuning method by using test discharge experiments. The new EKF technique pulls essential power of EKF and implements more accurate and stable estimation. This means that the accurate SOC estimation can be executed with a larger time step and less complex computation. Consequently, the accurate calculation does not need expensive computer. It is sufficient by an inexpensive microcomputer. Computation time for each EKF time step (1 s) was 4 ms.
Keywords :
Kalman filters; electric impedance; nonlinear filters; polynomial approximation; secondary cells; EKF technique; OCV-SOC curve; SOC estimation system; discrete-time system model; extended Kalman filter; external current; internal impedance; lithium-ion battery; noise tuning method; numerical analysis method; simple polynomial function; state of charge estimation system; test discharge experiment; time 4 ms; Batteries; Equations; Estimation; Mathematical model; Noise; System-on-chip; Vectors;
Conference_Titel :
Vehicle Power and Propulsion Conference (VPPC), 2014 IEEE
Conference_Location :
Coimbra
DOI :
10.1109/VPPC.2014.7007006