基于AUKF的锂离子电池SOC估计方法

doi:10.19562/j.chinasae.qcgc.2022.07.014

Abstract

Abstract:

A state of charge （SOC） estimation method of lithium-ion battery based on adaptive unscented Kalman filter （AUKF） is proposed in this paper. Firstly， the second-order RC equivalent circuit model of battery is established with its parameters identified. Then， aiming at the deficiency of unscented Kalman filter （UKF） algorithm， the convergence criterion for general filter is introduced， and the UKF algorithm is improved by the adaptive adjustment of measurement noise and process noise and the correction of Kalman gain， forming an AUKF-based SOC estimation method. Finally， verifications are performed with test data and public battery dataset， and the results show that the method proposed has fast convergence speed and high estimation accuracy.

Key words: lithium-ion battery, state of charge estimation, adaptive unscented Kalman filter

Ping Wang,Qingrui Gong,Ze Cheng,Ji’ang Zhang. An AUKF-Based SOC Estimation Method for Lithium-ion Battery[J].Automotive Engineering, 2022, 44(7): 1080-1088.

Figures/Tables 16

References 22

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SOC₀	0	0.2	0.4	0.6	0.8
MAE	0.008 5	0.006 3	0.003 2	0.003 0	0.001 6
RMSE	0.008 8	0.006 6	0.003 4	0.003 5	0.002 3
跟随系数	0.069 7	0.068 2	0.063 9	0.049 7	0.026 5

工况	AUKF			UKF
工况	MAE	RMSE	跟随系数	MAE	RMSE	跟随系数
US06	0.003 9	0.004 5	0.000 5	0.009 8	0.010 5	0.009 2
FUDS	0.008 1	0.008 2	0.007 0	0.013 8	0.015 1	0.077 1
BJDST	0.006 4	0.006 9	0.003 3	0.009 0	0.010 0	0.038 6

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An AUKF-Based SOC Estimation Method for Lithium-ion Battery

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