ECU Diagnostic Code Analyzer
Decode ECU diagnostic codes and generate targeted debugging strategies
What You Can Do
This skill enables you to rapidly decode ECU diagnostic trouble codes, cross-reference them with vehicle architecture and monitor logic, identify whether issues stem from firmware, calibration, hardware, or integration problems, and generate actionable debugging strategies. By automating DTC interpretation and fault tree analysis, you can compress weeks of manual cross-referencing into structured analysis that prioritizes root causes and reduces warranty costs.
Features
Interpret standard OBD-II codes and proprietary manufacturer codes with sensor thresholds and timing windows
Map dependencies across networked ECUs to identify single root causes triggering multiple DTCs
Distinguish between firmware logic issues, calibration parameter faults, hardware degradation, and integration problems
Debug onboard diagnostic monitor thresholds, timing windows, and false-positive triggers
Correlate DTC patterns across vehicle populations to identify systemic calibration or design issues
Produce prioritized test plans, lab reproduction steps, and dynamometer test procedures
Generate diagnostic guides and calibration release notes with code explanations and corrective actions
Link related DTCs to single root causes (e.g., fuel pressure + misfire DTCs from pump failure)
Example Output
Input: P0171 (System Too Lean Bank 1) + P0300 (Random Misfire Detected) triggered on 2024 model year vehicle
Output:
Primary Fault: Fuel Pump Pressure Below Threshold
├─ Monitor: Fuel Rail Pressure Monitor (threshold: 45-65 psi)
├─ Sensor Signal: Fuel pressure sensor reading 38 psi at idle (below 45 psi threshold)
├─ Actuator Impact: Injector pulse width compensation insufficient → lean air-fuel ratio
├─ Secondary Effect: Misfire detection triggered during idle stability test
└─ Root Cause: Fuel pump relay circuit voltage drop OR fuel pump degradation
Recommended Debugging Steps:
1. Measure fuel pump relay output voltage (expect 12V+)
2. Check fuel pump current draw (typical: 4-6A at idle)
3. Inspect fuel filter pressure drop across element
4. Validate fuel rail pressure sensor calibration ±2%
5. Run fuel pump endurance test at 50°C/120°F for 30 minutes
Input: Cabin electronics ECU reports P1234 (Proprietary: CAN Message Timeout from Powertrain ECU)
Output:
Comm Fault: Powertrain ECU Not Transmitting on CAN Bus
├─ Expected Message: PWR_ECU_Status (500 ms cycle time)
├─ Detection Logic: Cabin ECU timeout monitor fires after 2 missing cycles
├─ Network Impact: Loss of engine speed, load, and diagnostic enable signals
└─ Probable Sources: CAN transceiver fault | Powertrain ECU watchdog reset | Wiring open/short
Testing Strategy:
• Oscilloscope: Capture CAN_H/CAN_L signals during key-on, verify 500 kbps bitrate
• Bench test: Powertrain ECU standalone with CAN message generator
• HIL simulation: Inject CAN timeout fault to verify timeout logic threshold
What's Included
- ecu-diagnostic-code-analyzer.md: Core instruction file with DTC decoding methodology, fault tree analysis framework, and debugging prioritization logic
- DTC Cross-Reference Template: Standardized worksheet mapping OBD-II and manufacturer codes to monitor logic, thresholds, and root cause categories
- Fault Tree Analysis Checklist: Step-by-step guide for tracing dependent DTCs across networked ECUs and identifying primary vs. secondary faults
- Debug Strategy Worksheet: Framework for generating lab reproduction steps, test point measurements, and dynamometer procedures
- Fleet Pattern Analysis Matrix: Template for correlating DTC frequency across vehicle populations by model year, production week, and calibration version
Who It's For
- Automotive Embedded Software Engineers — Diagnosing firmware logic issues and monitor threshold tuning during calibration development
- Powertrain/Chassis System Engineers — Identifying root causes in ECU architectures and CAN network integration
- Field Service Technicians — Rapidly triaging vehicle DTCs and prioritizing repair procedures to reduce downtime
- Calibration Engineers — Debugging false-positive DTC triggers and optimizing monitor thresholds post-release
- Quality & Warranty Analysts — Analyzing fleet DTC patterns to identify systemic issues and manage recall campaigns
Best For
- Field vehicle DTC rapid root cause analysis during warranty investigation
- Lab and dynamometer testing to reproduce DTCs under controlled conditions
- Debugging monitor logic that generates false positives or missed faults
- Prioritizing which DTCs to address in calibration release cycles
- Creating DTC documentation and diagnostic strategy guides for service networks
You might also like
You can validate AUTOSAR software architectures across multiple compliance dimensions—layer separation, component interfaces, port definitions, service interfaces, and communication semantics. The skill identifies structural violations, missing documentation artifacts, and compliance gaps early in the design phase, helping you catch issues before formal gates and functional safety audits. It generates architecture compliance reports and documentation needed for ISO 26262 functional safety reviews.
You can design complete AUTOSAR 4.x system architectures by automating component allocation across abstraction layers, modeling port interactions and service interfaces, and validating compliance with AUTOSAR standards. Claude helps you create standardized architecture documentation, detect circular dependencies and interface mismatches, and generate port interaction matrices—accelerating ECU architecture development while ensuring standards adherence.
You can analyze FEA thermal simulation data to identify motor hotspots, calculate heat generation from motor losses across operating points, evaluate competing cooling solutions quantitatively, and troubleshoot excessive temperature rise during dyno testing. The skill helps you validate thermal management design margins, assess motor lifetime degradation risk, and optimize cooling loop efficiency—enabling data-driven thermal design decisions before building prototypes.
You can efficiently diagnose complex NVH concerns by working through a structured framework that correlates customer symptoms with potential powertrain failures. This skill helps you narrow diagnostic possibilities, recommend targeted testing sequences, distinguish between component failures and tuning issues, and substantiate warranty claims with technical evidence.
You can evaluate simulation scenarios against functional safety and SOTIF requirements, identify untested edge cases and high-risk operational design domains, map failure modes to root causes, and generate traceability matrices linking requirements to validation results. This skill transforms raw simulation data into defensible technical documentation that demonstrates test completeness and readiness for real-world deployment.
You can pinpoint the exact source of sensor fusion failures—whether they stem from misaligned camera/LiDAR/radar extrinsic calibration, timestamp desynchronization, data validation gaps, or algorithmic issues. This skill decomposes multi-modal perception errors into sensor-specific contributions and generates quantifiable diagnostic reports that directly guide calibration and testing teams toward fixes rather than blind troubleshooting.
You can quantify sensor fusion performance across object detection, classification, tracking, and localization using standardized metrics. The framework helps you identify systematic failure modes in diverse environmental conditions, document safety-critical gaps, and generate structured evidence packages for ISO 26262 and SOTIF compliance. This enables you to benchmark sensor configurations, define perception KPIs, and support regulatory submissions with rigorous performance documentation.
You can analyze multi-dimensional steering system performance including torque characteristics, self-alignment torque, steering angle feedback, road feel transmission, and torque vectoring effects. Extract actionable insights from simulation and test data to identify root causes of steering feel issues, then develop tuning recommendations for steering gear ratios, EPS algorithms, suspension geometry effects, and torque vectoring control strategies.