Python(编程语言)
计算机科学
元数据
软件
解析
分析
操作系统
数据库
嵌入式系统
人工智能
作者
Patrick Herring,Chirranjeevi Balaji Gopal,Muratahan Aykol,Joseph H. Montoya,Abraham Anapolsky,Peter M. Attia,William E. Gent,Jens S. Hummelshøj,Linda Hung,Ha-Kyung Kwon,Patrick Moore,Daniel Schweigert,Kristen Severson,Santosh K. Suram,Zi Yang,Richard D. Braatz,Brian D. Storey
出处
期刊:SoftwareX
[Elsevier BV]
日期:2020-01-01
卷期号:11: 100506-100506
被引量:45
标识
DOI:10.1016/j.softx.2020.100506
摘要
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.
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