Estimation of the SOC of lithium batteries based on an improved CDKF algorithm

doi:10.19799/j.cnki.2095-4239.2021.0124

Abstract

Abstract:

Accurate estimation of the SOC can provide a basis for balanced management between batteries and extend the overall service life of a lithium battery pack. In order to address large linear errors in the central differential Kalman filter algorithm (CDKF), an improved CDKF algorithm is proposed. The iterative filtering idea is introduced in the original algorithm, and the measurement information is used to constantly update the estimated value of the state. The observation information is provided iteratively, and the covariance matrix is continuously modified based on the LM optimization method, which effectively reduces the linear error. Based on the second-order resistance-capacitance circuit unit model, the least square parameter identification method is selected to identify the model resistance and capacitance parameters, then HPPC experiments are performed to verify the accuracy of the battery equivalent model. Finally, the improved CDKF algorithm is applied to estimate the SOC and voltage under both constant current conditions and dynamic conditions, and the estimation results are compared to the CDKF algorithm. The results show that the improved CDKF algorithm has higher accuracy, the SOC estimation accuracy can be improved by 1.16%, the maximum error is less than 1.7%, and the algorithm convergence time is shorter than the original algorithm. This improved CDKF algorithm improves the estimation accuracy and robustness and offers numerous application advantages.

Key words: state of charge, central differential Kalman filter, parameter identification, LM optimization method

CLC Number:

TM 912

Xiaoli ZHANG, Yuetong WANG, Jinsong XIA, Yingying ZHANG. Estimation of the SOC of lithium batteries based on an improved CDKF algorithm[J]. Energy Storage Science and Technology, 2021, 10(4): 1454-1462.

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指标	ICR18650-26锂电池数值
额定容量/mA·h	2600
额定电压/V	3.7
上限电压/V	4.2
下限电压/V	2.75
温度范围/℃	-40～65

算法		CDKF	改进的CDKF
电压	RMSE(10^-5)	3.14	1.17
电压	MAE	0.0045	0.0027
SOC	RMSE(10^-5)	5.55	3.12
SOC	MAE	0.0066	0.0050

算法		CDKF	改进的CDKF
电压	RMSE(10^-5)	5.03	2.31
电压	MAE	0.0057	0.0039
SOC	RMSE(10^-5)	21.5	12.1
SOC	MAE	0.0255	0.0193

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