关键词: 电化学阻抗谱, 温度估算, 锂离子电池, BMS

Abstract:

The widespread application of lithium-ion batteries in new energy vehicles and energy storage presents challenges in accurately estimating their internal states, particularly the temperature within the battery core, which is crucial for thermal runaway prediction. This paper reviews classical sensor-less methods for battery temperature detection and introduces a temperature estimation approach based on electrochemical impedance spectroscopy (EIS). Moreover, this study investigates the influence of internal battery parameters on temperature estimation using EIS and analyzes the relationship between impedance magnitude, phase angle, and temperature for high-capacity ternary lithium-ion power batteries at different frequencies. A model for the online temperature estimation of lithium-ion batteries based on EIS is proposed, which achieves an accurate estimation of the internal battery temperature by analyzing the relationship between the magnitude of the impedance, phase angle, and temperature at different frequencies. The study indicates that a frequency point of 10 Hz is suitable for estimating temperature using impedance magnitude information, while a frequency point of 17.5 Hz is suitable for estimating temperature using impedance phase angle information. Within the range of -20 ℃ to 45 ℃, the maximum temperature estimation errors obtained when using the impedance magnitude and impedance phase angle are 3.79 ℃ and 2.69 ℃, respectively. Validation results demonstrate that the use of the impedance spectrum magnitude and phase angle information effectively estimates the true internal temperature of the battery. This study helps to improve the acquisition function of automotive BMS, which can be used to improve the management strategy of battery thermal management and thermal runaway.

Key words: electrochemical impedance spectroscopy, temperature estimation, lithium ion battery, BMS