Electrochemical Impedance Spectroscopy (EIS) is a method used for estimating battery states (SoX) through the measurement of battery impedance, allowing rapid and accurate monitoring of Li-ion batteries (LIBs). Safe operation of LIBs is critical to optimizing battery performance across all application use cases.

The practical application of EIS, on both Electric Vehicles (EVs) and Battery Energy Storage Systems (BESSs), can further complement current Battery Management System (BMS) data-driven algorithms, enabling better operation of existing LIBs by providing accurate State of Charge (SoC), State of Health (SoH) and State of Temperature (SoT) estimation.
Moreover, EIS enables thermal runaway (TR) prediction, thereby enhancing the safety capabilities of current BMS implementations.

This work presents a Demonstrator Platform showcasing ST products (MCU, BMS ICs) performing EIS in real operating conditions. The associated software package controls the acquisition and excitation sub-systems and performs post-processing activities. The proposed setup, designed for simplicity, is used to properly evaluate battery impedance over a 5-cell battery module.

SoT estimation has been validated on this setup at different temperatures, both with and without parallel excitation (WLTC profile) generated by a bidirectional DC power supply. SoT estimation demonstrates a linear correlation with battery temperature in all conditions.

The proposed setup successfully implemented EIS. Optimal SoT frequency is identified and used with RMSE below 2°C both in idle and under load conditions.
This work details the setup, hardware, algorithms, software, and the results obtained in measuring battery impedance and performing SoT estimation.