MagBridge-Battery: Synthetic Battery Magnetometry Data with Degradation Labels

An open synthetic dataset for battery research. It contains magnetometry measurements paired with labels indicating battery degradation. The dataset was published on Kaggle, but details on its creator, size, and specific collection period are not provided.

Use Cases

• Predicting battery degradation states based on synthetic magnetometry signals.
• Training models for battery health monitoring using labeled synthetic data.
• Benchmarking anomaly detection algorithms for battery failure prediction.
• Developing digital twins for battery systems using simulated sensor data.

Strengths

• It is described as the first open synthetic dataset of its kind for battery magnetometry.
• Includes explicit degradation labels, which are crucial for supervised learning tasks.

Limitations

• Row count, column definitions, and file formats are unknown, limiting suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Kaggle

Collection Method

Synthetically generated, as stated in the description.

Time Range

null

Freshness

Last update date is unknown; freshness unverified.

Geography

null