Electrochemical Impedance Spectroscopy-Based Characterization and Modeling of Lithium-Ion Batteries Based on Frequency Selection

Abstract

Lithium-ion batteries are commonly employed in electric vehicles due to their efficient energy storage and conversion capabilities. Nevertheless, to ensure reliable and cost-effective operation, their internal states must be continuously monitored. Electrochemical impedance spectroscopy (EIS) is an effective tool for assessing the battery’s state. Different frequency ranges of EIS correspond to various electrochemical reaction processes. In this study, EIS measurements were conducted at seven temperatures, ranging from −20 °C to 10 °C, and across 21 states of charge (SOCs), spanning from 0% to 100%. A regression model was utilized to examine the unidirectional factorial characteristic impedance relative to temperature and SOC. An analysis of variance (ANOVA) table was created with temperature and SOC as independent variables and the impedance value as the dependent variable. These models accurately capture the behavior of lithium-ion batteries under different conditions. Based on this research, the battery electrochemical processes are better understood. This paper establishes a mathematical expression for a temperature–SOC-based impedance model at specific frequencies, i.e., 1 Hz, 20 Hz, and 3100 Hz. When comparing the models at these three frequencies, it was found that the model fitting accuracy is highest at 20 Hz, making it applicable across a wide range of temperatures and SOCs. Consequently, the accuracy of the impedance model can be enhanced at a specific frequency, simplifying the impedance model and facilitating the development of advanced battery state estimation methods.