DATTES: Data analysis tools for tests on energy storage
Eduardo Redondo-Iglesias,
Marwan Hassini,
Pascal Venet,
Serge Pelissier
Affiliations
Eduardo Redondo-Iglesias
Univ Lyon, Univ Eiffel, ENTPE, LICIT-ECO7 Lab, 69500 Bron, France; ERC GEST (Eco7/Ampère Joint Research Team for Energy Management and Storage for Transport), 69500 Bron, France; Corresponding author at: Univ Lyon, Univ Eiffel, ENTPE, LICIT-ECO7 Lab, 69500 Bron, France.
Marwan Hassini
Univ Lyon, Univ Eiffel, ENTPE, LICIT-ECO7 Lab, 69500 Bron, France; Univ Lyon, Université Claude Bernard Lyon 1, INSA Lyon, Ecole Centrale de Lyon, CNRS, Ampère, UMR5005, 69622 Villeurbanne, France; ERC GEST (Eco7/Ampère Joint Research Team for Energy Management and Storage for Transport), 69500 Bron, France
Pascal Venet
Univ Lyon, Université Claude Bernard Lyon 1, INSA Lyon, Ecole Centrale de Lyon, CNRS, Ampère, UMR5005, 69622 Villeurbanne, France; ERC GEST (Eco7/Ampère Joint Research Team for Energy Management and Storage for Transport), 69500 Bron, France
Serge Pelissier
Univ Lyon, Univ Eiffel, ENTPE, LICIT-ECO7 Lab, 69500 Bron, France; ERC GEST (Eco7/Ampère Joint Research Team for Energy Management and Storage for Transport), 69500 Bron, France
Experiments are essential to understand the behaviour and performance of energy storage systems. In this field, a considerable amount of experimental data is generated and data processing is a tedious task. To date, research teams working in the field of energy storage tend to focus on developing their own analysis tools rather than using existing open source software. This strategy can be detrimental to the quality and reproducibility of the research. This paper presents DATTES, a free and open source software for analysing experimental battery data. The software provides a comprehensive and customizable toolkit for extracting, analysing and visualizing experimental data. It also creates gateways to other open software and tools. In this way, DATTES enables users to get the most out of their experimental data and engage in open and reproducible science.
