Electrochemical Impedance Spectroscopy Processing and Modelling for Lithium-ion Batteries Using Python and Jupiter

Abstract

This paper describes how to model a Lithium-ion battery’s internal characteristics based on electrochemical impedance spectroscopy (EIS) data and their fitting into an Equivalent Circuit Model (ECM) using Python and the Jupyter development environment. The described method is used on an extensive dataset collected during an ageing campaign of lithium-ion batteries. The work aims to determine the correct values of ECM elements with satisfactory accuracy. The battery’s ECM parameter interpretation provides essential information about its internal structure and mechanisms, which helps to understand its processes and estimate its future degradation. It was necessary to deal with two tasks: first, the processing of many measurements, and second, estimating the appropriate input parameters for the ECM. We have managed to practically automate the processing of more than one thousand files with measured data and design and gradually refine a method for estimating input parameters for ECM fitting.