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Energies 2018, 11(1), 209; https://doi.org/10.3390/en11010209

A New Method for State of Charge Estimation of Lithium-Ion Batteries Using Square Root Cubature Kalman Filter

1
State Key Laboratory of Advanced Design and Manufacture for Vehicle Body, Hunan University, Changsha 410082, China
2
Haima Automobile Group Co., Ltd., Haikou 570216, China
3
Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 430070, China
*
Author to whom correspondence should be addressed.
Received: 22 December 2017 / Revised: 2 January 2018 / Accepted: 8 January 2018 / Published: 15 January 2018
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Abstract

State of charge (SOC) is a key parameter for lithium-ion battery management systems. The square root cubature Kalman filter (SRCKF) algorithm has been developed to estimate the SOC of batteries. SRCKF calculates 2n points that have the same weights according to cubature transform to approximate the mean of state variables. After these points are propagated by nonlinear functions, the mean and the variance of the capture can achieve third-order precision of the real values of the nonlinear functions. SRCKF directly propagates and updates the square root of the state covariance matrix in the form of Cholesky decomposition, guarantees the nonnegative quality of the covariance matrix, and avoids the divergence of the filter. Simulink models and the test bench of extended Kalman filter (EKF), Unscented Kalman filter (UKF), cubature Kalman filter (CKF) and SRCKF are built. Three experiments have been carried out to evaluate the performances of the proposed methods. The results of the comparison of accuracy, robustness, and convergence rate with EKF, UKF, CKF and SRCKF are presented. Compared with the traditional EKF, UKF and CKF algorithms, the SRCKF algorithm is found to yield better SOC estimation accuracy, higher robustness and better convergence rate. View Full-Text
Keywords: lithium-ion batteries; state of charge (SOC); square root cubature Kalman filter (SRCKF); electric vehicle (EV); real-time estimation lithium-ion batteries; state of charge (SOC); square root cubature Kalman filter (SRCKF); electric vehicle (EV); real-time estimation
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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. (CC BY 4.0).
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Cui, X.; Jing, Z.; Luo, M.; Guo, Y.; Qiao, H. A New Method for State of Charge Estimation of Lithium-Ion Batteries Using Square Root Cubature Kalman Filter. Energies 2018, 11, 209.

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