| Standard | Purpose | Physical Layer | Max Speed |
|---|---|---|---|
| OBD-II (ISO 15031) | Standardised diagnostic access; emission-related DTCs | SAE J1962 connector; CAN (ISO 15765-4) | 500 kbit/s CAN |
| UDS (ISO 14229) | Unified Diagnostic Services; 26 service IDs | CAN, Ethernet, LIN | Depends on physical layer |
| DoIP (ISO 13400) | Diagnostics over IP; tester connects via Ethernet | Ethernet (100BASE-T1 or 1000BASE-T1) | 1 Gbit/s |
| SOVD (ISO 23800) | Service-Oriented Vehicle Diagnostics; REST API | Ethernet / HTTP/2 | 1 Gbit/s |
OBD-II and DoIP Standards
UDS Diagnostic Routing
"""UDS diagnostic routing table for zone architecture."""
# Each ECU has a logical address (CAN: 11-bit; DoIP: 16-bit)
# Gateway routes UDS requests from tester to target ECU
UDS_ROUTING_TABLE = [
# ECU Name Phys Addr Func Addr Protocol Bus
{"ecu": "HPC_ADAS", "phys":0x0040, "func":0x7DF, "proto":"DoIP", "bus":"ETH_BACKBONE"},
{"ecu": "GW_ECU", "phys":0x0001, "func":0x7DF, "proto":"DoIP", "bus":"ETH_BACKBONE"},
{"ecu": "ZONE_FRONT_L", "phys":0x0710, "func":0x7DF, "proto":"UDS_CAN","bus":"CAN_ZONE_FL"},
{"ecu": "ZONE_FRONT_R", "phys":0x0720, "func":0x7DF, "proto":"UDS_CAN","bus":"CAN_ZONE_FR"},
{"ecu": "ZONE_REAR", "phys":0x0730, "func":0x7DF, "proto":"UDS_CAN","bus":"CAN_ZONE_R"},
{"ecu": "LEGACY_EPS", "phys":0x0018, "func":0x7DF, "proto":"UDS_CAN","bus":"CAN_CHASSIS"},
]
def find_route(target_addr: int) -> dict:
"""Find routing entry for a target ECU address."""
for entry in UDS_ROUTING_TABLE:
if entry["phys"] == target_addr:
return entry
return {"error": f"No route for addr 0x{target_addr:04X}"}
print("Diagnostic routing table:")
for e in UDS_ROUTING_TABLE:
print(f" {e['ecu']:<20} phys=0x{e['phys']:04X} {e['proto']} on {e['bus']}")Summary
Diagnostic network planning is often treated as an afterthought in architecture projects -- "we will add the OBD connector and route diagnostics through the gateway at the end". This approach consistently causes integration problems because diagnostic routing affects every ECU's address assignment, the gateway routing table, and the workshop tool configuration. DoIP is the correct modern architecture: connecting the factory and workshop tester directly to the Ethernet backbone enables simultaneous flashing of all ECUs at Gigabit speeds (a full vehicle flash in under 10 minutes vs 90+ minutes on CAN), and the DoIP entity address assignment must be part of the initial architecture before any ECU software is developed.
🔬 Deep Dive — Core Concepts Expanded
This section builds on the foundational concepts covered above with additional technical depth, edge cases, and configuration nuances that separate competent engineers from experts. When working on production ECU projects, the details covered here are the ones most commonly responsible for integration delays and late-phase defects.
Key principles to reinforce:
- Configuration over coding: In AUTOSAR and automotive middleware environments, correctness is largely determined by ARXML configuration, not application code. A correctly implemented algorithm can produce wrong results due to a single misconfigured parameter.
- Traceability as a first-class concern: Every configuration decision should be traceable to a requirement, safety goal, or architecture decision. Undocumented configuration choices are a common source of regression defects when ECUs are updated.
- Cross-module dependencies: In tightly integrated automotive software stacks, changing one module's configuration often requires corresponding updates in dependent modules. Always perform a dependency impact analysis before submitting configuration changes.
🏭 How This Topic Appears in Production Projects
- Project integration phase: The concepts covered in this lesson are most commonly encountered during ECU integration testing — when multiple software components from different teams are combined for the first time. Issues that were invisible in unit tests frequently surface at this stage.
- Supplier/OEM interface: This is a topic that frequently appears in technical discussions between Tier-1 ECU suppliers and OEM system integrators. Engineers who can speak fluently about these details earn credibility and are often brought into critical design review meetings.
- Automotive tool ecosystem: Vector CANoe/CANalyzer, dSPACE tools, and ETAS INCA are the standard tools used to validate and measure the correct behaviour of the systems described in this lesson. Familiarity with these tools alongside the conceptual knowledge dramatically accelerates debugging in real projects.
⚠️ Common Mistakes and How to Avoid Them
- Assuming default configuration is correct: Automotive software tools ship with default configurations that are designed to compile and link, not to meet project-specific requirements. Every configuration parameter needs to be consciously set. 'It compiled' is not the same as 'it is correctly configured'.
- Skipping documentation of configuration rationale: In a 3-year ECU project with team turnover, undocumented configuration choices become tribal knowledge that disappears when engineers leave. Document why a parameter is set to a specific value, not just what it is set to.
- Testing only the happy path: Automotive ECUs must behave correctly under fault conditions, voltage variations, and communication errors. Always test the error handling paths as rigorously as the nominal operation. Many production escapes originate in untested error branches.
- Version mismatches between teams: In a multi-team project, the BSW team, SWC team, and system integration team may use different versions of the same ARXML file. Version management of all ARXML files in a shared repository is mandatory, not optional.
📊 Industry Note
Engineers who master both the theoretical concepts and the practical toolchain skills covered in this course are among the most sought-after professionals in the automotive software industry. The combination of AUTOSAR standards knowledge, safety engineering understanding, and hands-on configuration experience commands premium salaries at OEMs and Tier-1 suppliers globally.