Micro-Short Detection on NASA Battery Dataset
Identifying physical precursors to thermal runaway from voltage transition analysis. The review flagged 429 anomalous data points across the full lifecycle of cell B0005.
Cycle 2
First Alert
Anomaly detected when BMS shows 100% health.
429
Alerts
Micro-short precursors flagged across full lifecycle.
Ideal Deployment Profile
Reference study summary
BMS reports a healthy state while internal micro-shorts are already forming, with thermal runaway precursors accumulating silently.
Internal resistance profiling via Ohm's Law reveals voltage spikes during charge transitions as early as Cycle 2.
Operators receive hundreds of cycles of lead time to address thermal risk before capacity visibly degrades.
Methods used in this study
High-speed voltage transition detection
Per-cycle internal resistance series
Rolling baseline anomaly classification
2-sigma threshold alerting
What made this dataset hard
to review well
Micro-short precursors happen at timescales BMS cannot capture
Standard monitoring flags issues only after 80% SOH, which is too late for early intervention
No way to quantify thermal runaway risk from standard telemetry
How the review
was carried out
Review step
Charge-to-rest and discharge-to-rest voltage transition extraction
Review step
Delta-V / Delta-I instantaneous resistance computation per transition
Review step
Rolling 2-sigma anomaly classification on resistance trend
What this validation
confirmed
This public reference study confirmed the following signals and decision points in the dataset.
Turn this reference study into a scoped review
If the pattern looks familiar, start with a fixed-scope Verify review. That establishes the asset baseline before anyone decides whether Horizon belongs in the operating stack.