A high-precision SOC and temperature joint estimation method based on rapid prototype modeling

doi:10.19799/j.cnki.2095-4239.2025.0192

Abstract

Abstract:

Mining lithium-ion batteries face severe safety and reliability challenges under extreme working conditions in coal mines. Although high-precision physical modeling is a potential solution, traditional experimental methods are limited by high cost and risk, while mechanism-based models struggle to adapt to actual complex working conditions. To address this, a collaborative estimation framework based on digital twins is proposed. Taking a 228 Ah mining lithium-ion battery as the object, a battery characteristic characterization system considering multi-factor coupling of temperature, multiplicity, state of charge (SOC), and aging is established by improving the first-order RC equivalent circuit model. Based on the Simulink/Simscape multiphysics field co-simulation platform, a digital twin system integrating electrochemical, thermodynamic, and state estimation algorithms is constructed. The convective heat transfer, unscented Kalman filter (UKF), and extended Kalman filter (EKF) modules are integrated to perform comparative analyses of SOC and temperature joint estimation. The experimental results of UKF show that the maximum permissible errors (MPE) of SOC estimation under BBDST conditions are 0.3937%, 0.4347%, and 0.5067% at 25 ℃, 45 ℃, and 60 ℃, respectively, while the MPE of temperature estimation are 0.74 ℃, 1 ℃, and 0.9613 ℃. Under DST conditions, the MPE of SOC estimation are 0.1829%, 0.0034%, and 0.0035% at 25 ℃, 45 ℃, and 60 ℃, respectively, and the MPE of temperature estimation are 0.6 ℃, 0.9992 ℃, and 0.9740 ℃. The results confirm that the model possesses excellent temperature adaptability and generalization capability, serving as a reliable digital twin verification platform for next-generation intelligent battery management system (BMS) development. This provides significant theoretical value and broad engineering application prospects.

Key words: mining lithium-ion battery, digital twin, SOC and temperature joint estimation, Simulink/Simscape

CLC Number:

TP 391.9

Juqiang FENG, Chengzhi ZHANG, Yuhang CHEN. A high-precision SOC and temperature joint estimation method based on rapid prototype modeling[J]. Energy Storage Science and Technology, 2025, 14(9): 3567-3580.

Figures/Tables 23

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Table 1

Analysis of SOC estimation error under BBDST operating conditions"

估计方法	SOC范围	25 ℃		45 ℃		60 ℃
估计方法	SOC范围	RMSE/%	$δ m i n$ ~ $δ m a x$ /%	RMSE/%	$δ m i n$ ~ $δ m a x$ /%	RMSE/%	$δ m i n$ ~ $δ m a x$ /%
UKF	1~0.95	0.0090	-0.0162~-0.0090	0.0090	-0.0091~0.0090	0.0090	-0.0091~-0.009
	0.95~0.05	0.0078	-0.0246~0.0088	0.0078	-0.0090~0.0058	0.0078	-0.0090~0.0045
	0.05~0.01	0.1048	-0.3937~0.0775	0.1823	-0.4347~0.0316	0.2264	-0.5067~0.0290

EKF	1~0.95	0.0128	-0.0162~-0.0090	0.0098	-0.0106~0.0090	0.0091	-0.0091~-0.009
	0.95~0.05	0.0101	-0.0246~0.0127	0.0081	-0.0241~0.0072	0.0880	-0.2030~0.0042
	0.05~0.01	0.2145	-0.3937~0.4091	0.3102	-0.6726~0.4473	0.3519	-0.7899~0.4664

Table 1

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Table 2

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估计方法	SOC 范围	误差/%
估计方法	SOC 范围	RMSE	Min~Max
UKF	1~0.95	0.0034	-0.0035~-0.0034
	0.95~0.05	0.0021	-0.0035~0.0183
	0.05~0.01	0.0544	-0.1829~-0.0004

EKF	1~0.95	0.0180	-0.0283~-0.0034
	0.95~0.05	0.0150	-0.0454~0.0194
	0.05~0.01	0.1776	-0.5616~-0.0001

工况温度	估计方法	SOC 范围	误差/%
工况温度	估计方法	SOC 范围	RMSE	Min~Max
45 ℃	UKF	1~0.67	0.0033	-0.0034~-0.0033
45 ℃	EKF	1~0.67	0.0069	-0.0268~0.0140

60 ℃	UKF	1~0.67	0.0034	-0.0035~-0.0034
60 ℃	EKF	1~0.67	0.0069	-0.0531~-0.0030