Automotive Diagnostics Development Engineer
Course objective
- To equip automotive professionals with the essential knowledge and skills to manage vehicle diagnostics in modern vehicles effectively.
- Developing vehicle diagnostics software is a specialized field that combines automotive engineering knowledge with strong software development skills. You’ll typically need to understand in-vehicle communication protocols, embedded systems, and specific diagnostic standards.
Who should attend
- Software update/cybersecurity managers
- Software update/cybersecurity engineers
- Organization (SUMS) responsible
- Regulatory affairs specialists
- Anyone seeking an in-depth understanding of iso 24089 and its impact on the automotive industry
Certifications you can pursue
- Certified Automotive Software Update Manager
Automotive Diagnostics Development Engineer
Automotive Fundamentals
- Vehicle Systems: Understanding how engine, transmission, braking, safety (ABS, airbags), infotainment, and ADAS systems work at a functional level.
- Automotive Electrics & Electronics (E/E Architecture): Knowledge of sensors, actuators, ECUs, and the overall electrical system.
In-Vehicle Communication Protocols
- CAN Bus (Controller Area Network/CANFD Flexible data)
- CAN Bus (Controller Area Network):
- FlexRay
- Automotive Ethernet
- MOST (Media Oriented Systems Transport)
Automotive Diagnostic Protocols & Standards
- ISO 14229 UDS diagnostic services
- ISO 15765 UDS over CAN transport
- ISO 13400 UDS over IP (DoIP)
- ISO 15031 OBD-II (emissions related)
- SAE J1939 For heavy-duty vehicles (trucks, buses).
Vehicle Diagnostics & OTA
- UDS services and diagnostic session handling
- Flash bootloaders and software update flows
- Remote diagnostics, OTA update architecture
Tools & Technologies (Conceptual/Practical)
- Vector Tools (CANalyzer, CANoe):
- dSPACE, ETAS, NI
- Python/C#/Java Libraries: For developing custom diagnostic applications (e.g., CAN libraries).
- Databases: Storing diagnostic data, vehicle configurations.
- Cloud Platforms: AWS IoT, Azure IoT, Google Cloud for connected vehicle diagnostics.
Diagnostic Software Design Principles
- Requirements gathering for diagnostic software.
- Software architecture patterns for diagnostic applications.
- User interface (UI) and user experience (UX) considerations for diagnostic tools (even if not building one, understanding good design is key).
- Data storage and management for diagnostic logs.
ECU Data Structures & Interpretation
- Understanding Diagnostic Trouble Codes (DTCs) – format, status bytes, environmental data.
- Parameter Identifiers (PIDs) and how they map to sensor readings and internal ECU values.
- Freeze Frame Data.
- Custom data definitions (e.g., for OEM-specific diagnostics).
Software for ECU Flashing/Reprogramming
- Bootloaders and their role.
- Flash memory organization.
- Security Seed/Key algorithms (conceptual understanding of how these protect ECUs).
- Checksumming and verification during flashing.
- Over-the-Air (OTA) updates – the software challenges.
Cybersecurity in Diagnostics
- Threats to diagnostic communication (e.g., unauthorized access, data manipulation).
- Authentication and authorization mechanisms (e.g., security access levels).
- Encryption and secure communication.
- Secure boot and secure flashing.
Case Studies & Practical Exercises
- Analyze real-world diagnostic logs and identify potential software issues or data interpretations.
- Design a simplified diagnostic application architecture.
- Write pseudo-code or actual code snippets to parse CAN messages or UDS responses.
- Simulate a diagnostic session using software tools (e.g., CANoe or a custom script interacting with a simulated ECU).