Lithium–Ion Battery Data: From Production to Prediction

Abstract

In our increasingly electrified society, lithium–ion batteries are a key element. To design, monitor or optimise these systems, data play a central role and are gaining increasing interest. This article is a review of data in the battery field. The authors are experimentalists who aim to provide a comprehensive overview of battery data. From data generation to the most advanced analysis techniques, this article addresses the concepts, tools and challenges related to battery informatics with a holistic approach. The different types of data production techniques are described and the most commonly used analysis methods are presented. The cost of data production and the heterogeneity of data production and analysis methods are presented as major challenges for the development of data-driven methods in this field. By providing an understandable description of battery data and their limitations, the authors aim to bridge the gap between battery experimentalists, modellers and data scientists. As a perspective, open science practices are presented as a key approach to reduce the impact of data heterogeneity and to facilitate the collaboration between battery scientists from different institutions and different branches of science.