SOC of estimation of lithium battery based on IBA-PF

doi:10.19799/j.cnki.2095-4239.2020.0175

Abstract

Abstract:

Aiming at the problem of particle dilution in traditional particle filter (PF) estimations of the state of charge (SOC), an improved bat algorithm (IBA) is proposed to optimize the PF algorithm to estimate the SOC. The particles are represented as bat individuals, which imitate the predatory process of a bat population and solve the problem of particle dilution in PF technology. The theoretical model of the battery state space is built using a second-order Thevenin battery model, and the relevant parameters of the battery are identified. The SOC estimation experiment is carried out based on the IBA-PF algorithm and the standard PF algorithm under pulse current operating conditions and dynamic stress test operating conditions. The experimental results show that, compared to the traditional PF algorithm, the estimation accuracy of the lithium battery SOC based on IBA-PF is within 2%, which indicates good adaptability and stability for non-linear and non-Gaussian SOC estimations of lithium batteries.

Key words: lithium battery, state of charge, bat algorithm, particle filte

CLC Number:

TM 912

Dongdong TIAN, Liwei LI, Yuxin YANG, Kai WANG. SOC of estimation of lithium battery based on IBA-PF[J]. Energy Storage Science and Technology, 2020, 9(5): 1585-1592.

Figures/Tables 16

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SOC	R₀	R₁	R₂	C₁	C₂
100	21.07	4.59	35.26	610.21	1643.75
90	28.32	4.79	30.31	573.43	1657.84
80	27.15	5.23	34.35	568.76	1498.32
70	27.38	4.95	36.87	601.32	1381.23
60	25.67	4.36	38.45	670.53	1170.65
50	28.38	3.12	21.36	880.41	1619.23
40	29.76	3.34	22.43	1142.56	2051.45
30	30.26	2.89	27.41	638.36	1676.32
20	30.86	4.63	29.36	301.45	1521.34
10	35.76	12.32	32.34	32.56	1186.42

算法	均方根误差/%	最大误差/%	平均误差/%
PF	1.95020915	2.634270147	1.08149597
IBA-PF	0.54384521	1.097486953	0.471425315

算法	均方根误差/%	最大误差/%	平均误差/%
PF	2.35146515	4.808587634	1.513773943
IBA-PF	0.74210396	1.944747621	0.52635715

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