State of Charge Estimation of Battery Energy Storage Systems Based on Adaptive Unscented Kalman Filter With a Noise Statistics Estimator

Since the noise statistics of large-scale battery energy storage systems (BESSs) are often unknown or inaccurate in actual applications, the estimation precision of state of charge (SOC) of BESSs using extended Kalman filter (EKF) or unscented Kalman filter (UKF) is usually inaccurate or even diverg...

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Bibliographic Details
Published in:IEEE access 2017-01, Vol.5, p.13202-13212
Main Authors: Peng, Simin, Chen, Chong, Shi, Hongbing, Yao, Zhilei
Format: Article
Language:English
Subjects:
Adaptive filters
Adaptive systems
Adaptive unscented Kalman filter
Batteries
Battery charge measurement
battery energy storage systems
Covariance
Energy storage
Error analysis
Estimation
Extended Kalman filter
Integrated circuit modeling
Kalman filters
Noise
noise statistics estimator
State of charge
Statistics
Storage systems
Voltage measurement
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Summary:Since the noise statistics of large-scale battery energy storage systems (BESSs) are often unknown or inaccurate in actual applications, the estimation precision of state of charge (SOC) of BESSs using extended Kalman filter (EKF) or unscented Kalman filter (UKF) is usually inaccurate or even divergent. To resolve this problem, a method based on adaptive UKF (AUKF) with a noise statistics estimator is proposed to estimate accurately SOC of BESSs. The noise statistics estimator based on the modified Sage-Husa maximum posterior is aimed to estimate adaptively the mean and error covariance of measurement and system process noises online for the AUKF when the prior noise statistics are unknown or inaccurate. The accuracy and adaptation of the proposed method is validated by the comparison with the UKF and EKF under different real-time conditions. The comparison shows that the proposed method can achieve better SOC estimation accuracy when the noise statistics of BESSs are unknown or inaccurate.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2017.2725301