This release adds 4 notable features for engineering teams evaluating rollout.
Published 1mo
Monitoring & Metrics
✓ No known CVEs patched
✓ No known CVEs patched in this version
Topics
anomaly-detection
battery
bms
can-bus
dbc
electric-vehicle
+9 more
ev
grafana
j1939
lstm
machine-learning
prometheus
python
quality-assurance
soh-prediction
Summary
AI summaryIntroduces core QA engine, ML anomaly detection, SOH prediction, and real-time dashboard.
Full changelog
EV-QA-Framework v1.0.0
ML-powered QA Framework for Electric Vehicle Battery Systems.
Features
- Core QA engine with Pydantic validation
- ML anomaly detection (Isolation Forest)
- SOH prediction via LSTM (optional TensorFlow)
- CAN bus emulation (2.0B + J1939)
- Cell imbalance detection & analysis
- Thermal runaway prediction (rule + ML)
- Prometheus metrics + Grafana dashboard
- Real-time FastAPI dashboard with WebSocket
- DBC file import (Vector CANdb format)
- Docker deployment
- CI/CD via GitHub Actions
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Beta — feedback welcome: [email protected]