A Variational Bayesian and Huber-Based Robust Square Root Cubature Kalman Filter for Lithium-Ion Battery State of Charge Estimation

Jing Hou, He He, Yan Yang, Tian Gao and Yifan Zhang
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Jing Hou: School of Electronic and Information, Northwestern Polytechnical University, Xi’an 710072, China
He He: System Engineering Research Institute of CSSC, Beijing 100094, China
Yan Yang: School of Electronic and Information, Northwestern Polytechnical University, Xi’an 710072, China
Tian Gao: School of Electronic and Information, Northwestern Polytechnical University, Xi’an 710072, China
Yifan Zhang: School of Electronic and Information, Northwestern Polytechnical University, Xi’an 710072, China

Energies, 2019, vol. 12, issue 9, 1-23

Abstract: An accurate state of charge (SOC) estimation is vital for safe operation and efficient management of lithium-ion batteries. To improve the accuracy and robustness, an adaptive and robust square root cubature Kalman filter based on variational Bayesian approximation and Huber’s M-estimation (VB-HASRCKF) is proposed. The variational Bayesian (VB) approximation is used to improve the adaptivity by simultaneously estimating the measurement noise covariance and the SOC, while Huber’s M-estimation is employed to enhance the robustness with respect to the outliers in current and voltage measurements caused by adverse operating conditions. A constant-current discharge test and an urban dynamometer driving schedule (UDDS) test are performed to verify the effectiveness and superiority of the proposed algorithm by comparison with the square root cubature Kalman filter (SRCKF), the VB-based SRCKF, and the Huber-based SRCKF. The experimental results show that the proposed VB-HASRCKF algorithm outperforms the other three filters in terms of SOC estimation accuracy and robustness, with a little higher computation complexity.

Keywords: state of charge (SOC); lithium-ion battery; square root cubature Kalman filter (SRCKF); variational Bayesian approximation; Huber’s M-estimation; adaptive; robust (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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