Introduction¶

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BEEP is a set of tools designed to support Battery Evaluation and Early Prediction of cycle life corresponding to the research of the d3batt program and the Toyota Research Institute.

BEEP enables parsing and handling of electrochemical battery cycling data via data objects reflecting cycling run data, experimental protocols, featurization, and modeling of cycle life with machine learning. Currently BEEP supports:

Arbin Instruments cyclers
Novonix Group cyclers
MACCOR cyclers
BioLogic cyclers
Battery Archive data

With partial and forthcoming support for:

Indigo cyclers
Neware cyclers

BEEP provides a standardized interface for working with cycler data ranging in scale from a single file on a local laptop to running thousands of cycler files with massive throughput on large computing systems.

We are currently looking for experienced python developers to help us improve this package and implement new features. Please contact any of the maintainers for more information.

Installation¶

To a base install, do:

pip install beep

If you want to develop BEEP and run tests, clone the repo via git and use pip (or python setup.py develop) for an editable install:

git clone git@github.com:ToyotaResearchInstitute/BEEP.git
cd BEEP
pip install -e .[tests]

Testing¶

Make sure you have installed the required testing packages (see installation).

pytest beep

How to cite¶

If you use BEEP, please cite this article:

P. Herring, C. Balaji Gopal, M. Aykol, J.H. Montoya, A. Anapolsky, P.M. Attia, W. Gent, J.S. Hummelshøj, L. Hung, H.-K. Kwon, P. Moore, D. Schweigert, K.A. Severson, S. Suram, Z. Yang, R.D. Braatz, B.D. Storey, SoftwareX 11 (2020) 100506. https://doi.org/10.1016/j.softx.2020.100506