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Mathematical Problems in Engineering
Volume 2017, Article ID 5489356, 10 pages
https://doi.org/10.1155/2017/5489356
Research Article

State of Charge Estimation for Lithium-Ion Battery by Using Dual Square Root Cubature Kalman Filter

School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China

Correspondence should be addressed to Luping Chen; nc.ude.tpub@nehc_gnipul

Received 30 June 2017; Revised 22 October 2017; Accepted 6 December 2017; Published 24 December 2017

Academic Editor: Marek Lefik

Copyright © 2017 Luping Chen 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

The state of charge (SOC) plays an important role in battery management systems (BMS). However, SOC cannot be measured directly and an accurate state estimation is difficult to obtain due to the nonlinear battery characteristics. In this paper, a method of SOC estimation with parameter updating by using the dual square root cubature Kalman filter (DSRCKF) is proposed. The proposed method has been validated experimentally and the results are compared with dual extended Kalman filter (DEKF) and dual square root unscented Kalman filter (DSRUKF) methods. Experimental results have shown that the proposed method has the most balance performance among them in terms of the SOC estimation accuracy, execution time, and convergence rate.