The state of health (SoH) of lithium-ion cells is crucial for ensuring optimal performance in critical applications such as electric vehicles (EVs) and energy storage systems. This work presents a fast, non-invasive method for estimating SoH using Electrochemical Impedance Spectroscopy (EIS) and Equivalent Electrical Circuit (EEC) models. Unlike conventional methods requiring lengthy charge-discharge cycles, the EIS approach enables SoH estimation in just 2-5 minutes, significantly reducing the time (compared to the traditional 2-5 hours of testing) and the energy consumption (small amplitude AC signal required).

The technique correlates impedance parameters, such as internal resistances and capacitances, with the health status of the cells. This method not only estimates the remaining capacity but also provides insights into internal degradation processes, allowing for failure prediction and enhanced system safety. The approach is adaptable to different cell chemistries and formats and can be applied to individual cells or modules in series-parallel combinations. Application of this technology implies the whole life-cycling of the cell, at different conditions and configurations, along with complementary periodic EIS tests. Ageing of the cell will be correlated with the EEC parameters along the life cycle with the objective of creating a correlation model which predicts the SoH (with an error margin of 10%) from fast-high frequency EIS measurements.

This procedure aims to a final product which includes the database, the correlation model and the automatic software which measure and indicates the SoH of an unknow cell/module (less than 5 min/estimation). This facilitates cell reuse and reconditioning, extending the cell’s life cycle and reducing operational costs.