SOC estimation of aging lithium battery based on adaptive CKF

doi:10.19799/j.cnki.2095-4239.2020.0005

Abstract

Abstract:

The state of charge (SOC) of a lithium battery is an important parameter associated with electric vehicle system management and energy control. During SOC estimation, the changes in battery parameters and aging problems will considerably affect the results. Therefore, the recursive least square (RLS) algorithm is used to identify the parameters of the lithium battery model and update the battery capacity. The SOC of the lithium battery can be estimated based on the cubature Kalman filter (CKF). Further, the SOC can be accurately estimated by combining RLS and CKF even though this causes the battery parameters to changes. The accuracy of the proposed algorithm can be verified by estimating the SOC of the lithium iron phosphate battery online.

Key words: lithium battery, state of charge (SOC), ageing, CKF

CLC Number:

TM 912

ZHENG Tao, ZHANG Li, HOU Yangcheng, CHEN Wei. SOC estimation of aging lithium battery based on adaptive CKF[J]. Energy Storage Science and Technology, 2020, 9(4): 1193-1199.

Figures/Tables 7

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Table 1

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References 13

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估计方法	平均误差/%	最大误差/%	执行时间/s
CKF	0.68	0.92	0.472
UKF	0.87	1.37	1.024
EKF	0.96	1.48	0.387

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