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Journal of Applied Mathematics
Volume 2014, Article ID 348537, 10 pages
http://dx.doi.org/10.1155/2014/348537
Research Article

Estimation of State of Charge for Lithium-Ion Battery Based on Finite Difference Extended Kalman Filter

School of Electrical Engineering & Automation of Tianjin University, Tianjin 300072, China

Received 4 December 2013; Revised 24 February 2014; Accepted 10 March 2014; Published 3 April 2014

Academic Editor: Gongnan Xie

Copyright © 2014 Ze Cheng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

An accurate estimation of the state of charge (SOC) of the battery is of great significance for safe and efficient energy utilization of electric vehicles. Given the nonlinear dynamic system of the lithium-ion battery, the parameters of the second-order RC equivalent circuit model were calibrated and optimized using a nonlinear least squares algorithm in the Simulink parameter estimation toolbox. A comparison was made between this finite difference extended Kalman filter (FDEKF) and the standard extended Kalman filter in the SOC estimation. The results show that the model can essentially predict the dynamic voltage behavior of the lithium-ion battery, and the FDEKF algorithm can maintain good accuracy in the estimation process and has strong robustness against modeling error.