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Repository for the paper "Statistical learning for accurate and interpretable battery lifetime prediction"

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revisit-severson-et-al

NOTE: Please contact Prof. Richard Braatz, braatz@mit.edu, for access to the code repository associated with the Severson et al. publication in Nature Energy (available with an academic license). This repository is not directly related to the Nature Energy paper.

This repository contains code for our work entitled "Statistical learning for accurate and interpretable battery lifetime prediction", a follow-up paper to Severson et al. A permanent archive of this work on Zenodo is available here: DOI

Our key scripts and functions are summarized here:

  • featuregeneration.m: MATLAB script that generates capacity arrays from the battery dataset and exports them to csvs (stored in /data).
  • revisit-severson-et-al.ipynb: Python notebook containing most of the analysis and figure generation.
  • image_annotated_heatmap.py: Helper function from matplotlib (see docstring for source).

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Repository for the paper "Statistical learning for accurate and interpretable battery lifetime prediction"

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