Data-driven State-of-Health prediction for reused batteries in new applications

This dataset contains raw exports from a Battery Energy Storage System (BESS) studied in Data-driven State-of-Health prediction for reused batteries in new applications reseach project funded by Energimyndigheten (Swedish Energy Agency) , organized for open publication and reproducible analysis. It follows a consistent folder structure, CSV schemas, and naming conventions to support downstream processing without requiring proprietary systems. Each date-range folder (e.g., 230420-230516, 240501-241104) contains synchronized telemetry for cell, module, and string levels, with files such as db-export-cell.csv, db-export-module.csv, db-export-string.csv, and optional context tables like db-export-module-info.csv or modules.csv. Common columns include timestamps (hour, ISO-8601 with UTC offset), hierarchy identifiers (location, rack, string, module, cell), measurement metric, numeric value, and a quality flag is_filler. Later exports include extended fields such as voltage, temperature, and module_uuid. Example uses include joining module telemetry with static metadata, aggregating string-level power metrics, and constructing unique per-cell identifiers. Citation:Project: Data-Driven State-of-Health Prediction for Recycled Batteries in New ApplicationsInstitution: RISE Research Institutes of Sweden ABProject Manager: Lars FastResearchers: Lars Fast, Ellen Scott, Christian Casanova, Anis MoradiKouchiFunder: Energimyndigheten (Swedish Energy Agency)