battery-hub

AI Battery Lifecycle (v3)

Neeraj Sathish Kumar

State-of-health estimationTrained on experimental data

AI Battery Lifecycle (v3)

Estimates current-cycle state of health from the 4.0–3.6 V part of a discharge, validated on held-out batteries from NASA, CALCE and Oxford aging data.

Model details

Architecture
Ensemble of tabular models (20 evaluated)
Input
18 features from the 4.0–3.6 V portion of a discharge
Output
SOH
Training data
Experimental
Trained on
NASA PCoE; CALCE; Oxford Battery Degradation Dataset 1
Uncertainty
Not reported
Physics constraints
None
License
mit

Limitations

  • For research on lab aging data; not certified for battery management, charging control, safety decisions or field use.
  • Doesn't provide a validated RUL forecast.
  • Check cross-dataset errors before applying it to a new chemistry, manufacturer, sensor set or duty cycle.