A User-Friendly Environment for Battery Data Science

TL;DR

This paper introduces a user-friendly software environment that simplifies data management, cleaning, and analysis for battery scientists, integrating diverse data sources and enabling advanced analytics through Jupyter Notebooks.

Contribution

It presents a novel, accessible platform that bridges the gap between battery domain expertise and data science tools, enhancing productivity in battery research.

Findings

Supports ingestion of diverse battery test data sources

Streamlines routine data analysis tasks

Enables advanced analytics with Jupyter Notebook integration

Abstract

We report a user-friendly software environment for battery data science. It is designed to streamline data management, data cleaning, and data analysis to help bridge the gap between the domain expertise of most battery scientists and the tools needed as the field becomes increasingly data intensive. The software solution suitable for ingesting battery test data from disparate sources. By aggregating data in an intelligent way, users can streamline routine data analysis tasks and leverage Jupyter Notebook functionality to build advanced scripts and analytics, thereby making battery engineering teams more productive.