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BEEP: A Python library for Battery Evaluation and Early Prediction
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DOI：10.1016/j.softx.2020.100506.png)
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Abstract
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Battery evaluation and early prediction software package ( BEEP ) provides an open-source Python-based framework for the management and processing of high -throughput battery cycling data-streams. BEEPs features include file-system based organization of raw cycling data and metadata received from cell testing equipment, validation protocols that ensure the integrity of such data, parsing and structuring of data into Python-objects ready for analytics, featurization of structured cycling data to serve as input for machine-learning, and end-to-end examples that use processed data for anomaly detection and featurized data to train early-prediction models for cycle life. BEEP is developed in response to the software and expertise gap between cell-level battery testing and data-driven battery development. (C) 2020 The Authors. Published by Elsevier B.V.
Keywords:
Battery
Cycling experiments
Python
Data management
Machine-learning
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