The DATTES workflow in 6 function

DATTES aims to transform the raw experimental data into valuable processed results that can be used for visualisation, modeling and/or prediction. To reach this goal, six functions have been developed :

  1. dattes_prepare: the first function of the workflow consist in transforming the raw experimental data produced in a proprietary format by the cycler into a standard and open format. The chosen export file format is .xml file with a VEHLIB structure. Find more details regarding dattes_prepare*, here.

  2. dattes_structure: thanks to this the second function .xml files are interpreted and transformed into a DATTES structure. By default, the DATTES structure is saved as .mat file but other file formats are possible such as .csv or .json formats. Further reading about dattes_structure is available at this page.

  3. dattes_configure: with this third function, the test main variables (U,I,t) are segmented and a motif discovery is processed to detect the different test phases that will be processed.Further reading about dattes_configure is available at this page

  4. dattes_analyse: this fourth step is the featurization one. It consists in analysing the data to obtain key performance indicators of tha energy storage system e.g. capacity, equivalent resistance, impedance identification, open circuit voltage or incremental capacity. Further reading about dattes_analyse is available at this page.

  5. dattes_plot: this function is the visualisation one. It can be used at any step of the workflow for anomaly detection for instance. Further reading about dattes_plot is available at this page.

  6. dattes_export: Finally, the export function allows to store the analysis results into various files formats. This facilitate the DATTES’ interoperability with other existing softwares in the field. Further reading about dattes_export is available at this page.