State of Charge Estimation of Power Batteries Based on the Gas-liquid Dynamics Thermal Coupling Model

doi:10.3901/JME.2023.22.163

Abstract

Abstract: The analytical model usually plays a key role in accurately estimating the online state of charge(SOC) of the battery. The physical similarity principle between gas-liquid dynamics and electricity is analyzed. The internal relationship of the diffusion/equilibrium between gas molecules and lithium ions, and the mechanism of the observation quantity lagging behind state quantity between the gas-liquid system and lithium-ion batteries are studied. The parameter mapping relationship between gas-liquid dynamics and electricity is improved. A gas-liquid dynamics battery model directly coupled with temperature characteristics is established. According to the distribution characteristics of the temperature field and the principle of energy conservation during the operation of the battery, a gas-liquid dynamics thermal coupling model is constructed. Based on this model and extended Kalman filter algorithm, an efficient online SOC estimation method for lithium-ion batteries is designed. Taking the lithium-ion power battery with a built-in temperature sensor as the research object, under various constant current and dynamic test conditions, the maximum estimation errors of the internal temperature and online SOC of the battery are less than 1.2 K and 1.8%, respectively. The proposed online SOC estimation method has a good accuracy and a strong ability to resist the initial value error.

Key words: lithium-ion battery, gas-liquid dynamics model, gas-liquid dynamics thermal coupling model, state of charge

CLC Number:

TM912

CHEN Biao, JIANG Haobin, LI Huanhuan, ZHAO Qian, WANG Tiansi. State of Charge Estimation of Power Batteries Based on the Gas-liquid Dynamics Thermal Coupling Model[J]. Journal of Mechanical Engineering, 2023, 59(22): 163-175.

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