Time-Based EIS Approach for State-of-Charge Assessment of Li-Ion Battery Cells in Automotive Applications: A Simulation Study

This paper presents a simulation-based study on a time-domain electrochemical impedance spectroscopy (EIS) approach for the state-of-charge (SoC) assessment of lithiumion battery (LIB) cells in automotive applications. The proposed methodology is validated within a MATLAB simulation environment by implementing an equivalent circuit model and analyzing impulse response (IR) measurements under varying SoC and temperature conditions. The IR obtained from the simulated measurement system is compared against the ideal battery's equivalent circuit model, demonstrating a strong correlation. Despite lower accuracy at elevated temperatures, the approach remains effective in SoC estimation. To further validate its robustness, a narrow neural network (NN) model is trained on temperature-dependent IRs, achieving reliable SoC classification. These results confirm the feasibility of the proposed method for real-time battery monitoring, offering a potential alternative to conventional frequency-domain EIS techniques.