Public site has been updated with new features to improve the user experience. We have added datasets from Underwriters Labs, Purdue University, and the University of Michigan. The site has expanded from battery cycling data to battery abuse data.
An article outlining the history and development of Battery Archive was published in the blog Battery Bits.
Data from Battery Archive will be cross-posted in ENPOLITE - a new tool developed by RWTH Aachen for comparing batteries across energy, power, lifetime, and temperature. We are also working on integration with BEEP to facilitate parsing and featurization of data for their machine learning models.
Software package underlying BatteryArchive.org now available on github. The system is built around Redash, a robust open-source extract-transform-load engine. The present release also includes starter queries, a database, schema, and a data importer, and guidance on connecting to Jupyter Notebook.
Published a preprint that describes the architecture of Battery Archive. We are planning to release the software soon.
Datasets from Purdue, Underwriters Labs, RWTH Aachen, NASA, UC Berkeley, and University College London are in the pipeline.
Datasets from Oxford and CALCE have been uploaded and content from other institutions is in the pipeline. We’ve added pages to explain the Metadata used for tagging in the database, address FAQ, and highlight other excellent Resources for battery data analysis.
Site is launched publicly with datasets from Hawai’i Natural Energy Institute and Sandia National Labs. Data sets from other institutions are in the pipeline. Initial capabilities include filtering by basic metadata and visualization of efficiencies, capacity/energy, and voltage curves over time. The ability to model the data is currently being beta-tested.
V0 prototype completed and tested internally with database and UX support from Sandia National Labs.
Development of batteryarchive.org begins following the DOE Office of Electricity Energy Storage Program peer review. Presentations and conversations crystallize gaps in open battery data sharing and the ability to easily compare data between studies.
Based on https://github.com/battery-lcf