Experimental Cycling Data for Commercial 18650 Lithium-Ion Batteries

Experimental cycling data for three commercial 18650-type batteries (NCA, NCM, and NCM+NCA) supports research into data-driven capacity estimation. Each CSV file contains 9 columns of time-series measurements, including cycle time, voltage, current, and charge/discharge electricity, recorded under varying temperature and current rate conditions. The dataset accompanies a Nature Communications publication on estimating battery capacity from voltage relaxation profiles.

Use Cases

• Developing machine learning models for battery capacity estimation based on voltage relaxation features.
• Analyzing the impact of cycling conditions (temperature, current rate) on battery performance and degradation.
• Validating physics-based or empirical models of lithium-ion battery charge/discharge behavior.
• Benchmarking data-driven state-of-health (SOH) estimation methods against controlled experimental data.

Strengths

• Data is associated with a peer-reviewed publication in Nature Communications, indicating scientific rigor.
• Includes data from three distinct commercial battery chemistries (NCA, NCM, NCM+NCA) under controlled experimental conditions.
• Each data file contains a structured set of 9 time-series columns, enabling consistent analysis across cells.

Limitations

• Key metadata such as row count, total file size, and specific update dates are not provided across any source.
• The column list from the description contains apparent repetitions and inconsistencies (e.g., 'Q discharge/mA.h' listed twice, incomplete column names).
• Documentation is noted to be within a zip file, suggesting potential accessibility barriers for immediate understanding.

Provenance

Source

Karlsruhe Institute of Technology (Author: Jiangong Zhu)

Collection Method

Laboratory experimental cycling of commercial 18650 battery cells under controlled conditions.