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December 22, 2025via Discourse

LF Energy Battery Data Alliance Announces the Battery Data Format (BDF)

LF Energy Battery Data Alliance Announces the Battery Data Format (BDF)

San Francisco, December 22, 2025 — LF Energy announced that its Battery Data Alliance has released the Battery Data Format (BDF) to address fragmentation in battery data across institutions, vendors, and platforms. The format enables datasets to be shared, analyzed, and reproduced reliably throughout the battery ecosystem.

Building on Global Collaboration

Development incorporated contributions from leading institutions:

  • BattINFO Ontology: BDF aligns with terminology from Battery2030+ and BIG-MAP projects, ensuring consistent definitions and linked-data compatibility.
  • Faraday Institution's PyProBE and BDX: PyProBE, an open-source Python package developed at Imperial College London, validated BDF's column naming and metadata definitions. Faraday Institution is funding PyProBE modifications to adopt BDF-aligned naming and enable interoperability with BDX (Battery Data eXchange).
  • Microsoft Open Battery Dataset: Microsoft plans to release a high-quality battery dataset in BDF format for benchmarking, tooling development, and educational purposes.
  • Ohm BDF Converter: Ohm contributes a web-based converter tool enabling users to upload raw cycler data and download BDF-compliant CSV files, supporting major commercial cycler formats.
  • Largest Open Source Contribution (August 2025): A collaboration between Empa, ETH Zurich, EPFL, and SINTEF produced a dataset from 199 coin cell batteries — two common chemistries (NMC and LFP), each tested for 1,000 cycles under fully automated workflows.

Practical Design Across the Battery Lifecycle

BDF addresses two primary challenges:

  1. Data Consistency: A common format eliminates structural inconsistencies arising from software updates across labs and equipment brands.
  2. Model Compatibility: A unified format allows battery model developers to easily adapt models to accept BDF data, enabling scientists to experiment with multiple models without custom coding.

The format is designed as open, extensible, and implementation-agnostic, accommodating future growth as new chemistries, devices, and data types emerge.

Early Software Support

  • BDF Python Library for reading/writing datasets and validating metadata
  • Conversion tools for transforming vendor-specific formats into BDF
  • Reference visualization tools (web and notebook-based) for exploring datasets
  • Conversion to/from BDX to access PyProBE tools
  • Compatibility with PyBaMM, BattMo, and analysis platforms

A Shared Foundation

“BDF provides a common language for battery data — designed in the open and strengthened by contributions from across the global community. We encourage organizations of all sizes to participate and help advance a unified standard for the battery industry.”

— Gabe Hege, Chairperson, Battery Data Alliance

Public specification, documentation, examples, and reference datasets are available at batterydataalliance.energy. Organizations interested in participating may contact info@batterydataalliance.energy.