DAQ (Data Acquisition) Mode - Calibration & XCP Protocol

DAQ List Structure

DAQ List Hierarchy

  DAQ List 0 — event: event_10ms (10ms task trigger)
  ├── ODT 0 (Object Descriptor Table — one CAN frame / DAQ packet)
  │   ├── ODT Entry 0: engine_rpm     address=0x20004A00, size=2 bytes
  │   ├── ODT Entry 1: coolant_temp   address=0x20004A04, size=2 bytes
  │   └── ODT Entry 2: lambda_actual  address=0x20004A08, size=4 bytes (float)
  └── ODT 1
      ├── ODT Entry 0: boost_mbar     address=0x20004A0C, size=2 bytes
      └── ODT Entry 1: inj_pw_us      address=0x20004A10, size=2 bytes

  DAQ List 1 — event: event_100ms (100ms task trigger)
  └── ODT 0
      └── ODT Entry 0: battery_voltage  address=0x20005000, size=2 bytes

Hexdaq_setup_trace.txt

/* Allocate DAQ list dynamically: ALLOC_DAQ, ALLOC_ODT, ALLOC_ODT_ENTRY */
/* Step 1: Free all existing DAQ lists */
Tx: D6 00 00 00 00 00 00 00  /* FREE_DAQ */
Rx: FF 00 00 00 00 00 00 00

/* Step 2: Allocate 1 DAQ list with 1 ODT with 3 ODT entries */
Tx: D5 01 00 00 00 00 00 00  /* ALLOC_DAQ: count=1 list */
Rx: FF 00 00 00 00 00 00 00
Tx: D4 00 00 01 00 00 00 00  /* ALLOC_ODT: daq=0, count=1 ODT */
Rx: FF 00 00 00 00 00 00 00
Tx: D3 00 00 00 03 00 00 00  /* ALLOC_ODT_ENTRY: daq=0, odt=0, count=3 */
Rx: FF 00 00 00 00 00 00 00

Event Channels: Tying DAQ to ECU Tasks

Event Channel	Trigger	Period	Typical DAQ Variables
event_1ms	1 ms OS task	1 ms	Injection pulse-width, ignition angle, fast actuators
event_10ms	10 ms OS task	10 ms	Engine speed, lambda, boost pressure, throttle
event_100ms	100 ms OS task	100 ms	Coolant temp, battery voltage, NvM-sourced values
event_sync	External sync (e.g., crank trigger)	Variable	Angle-synchronous signals (BSFC per combustion cycle)

⚠️ Event Period Mismatch

Assigning a slow-changing variable (coolant_temp, updated every 100ms) to event_1ms wastes DAQ bandwidth — you get 100 identical values per second. Assign each MEASUREMENT to the event matching its update rate. Tools like INCA and CANape show the configured event channel per signal in the DAQ allocation view.

Static vs Dynamic DAQ

Feature	Static DAQ (A2L IF_DATA)	Dynamic DAQ (runtime allocation)
Definition	DAQ lists pre-defined in A2L	Allocated via ALLOC_DAQ commands at session start
Flexibility	Fixed groups, no runtime change	Arbitrary signal grouping per session
A2L change needed to add signal	Yes	No — drag new signal to existing DAQ list in tool
ECU RAM overhead	Pre-allocated (known at compile time)	Runtime allocated — must not exceed ECU DAQ memory budget
Typical use	Series production ECU (locked A2L)	Development ECU with evolving measurement needs

DAQ Overrun Detection

Pythondaq_overrun_check.py

# Check for DAQ overruns by monitoring sequence counter gaps
# Each DAQ packet contains a timestamp or sequence counter

import mdf4reader as mdf

recording = mdf.load("bench_run_001.mf4")
daq_channel = recording.get_channel("XCP_DAQ_SEQUENCE_CTR")

samples = daq_channel.samples
timestamps = daq_channel.timestamps

overruns = []
for i in range(1, len(samples)):
    expected_delta = 1   # sequence counter increments by 1 per packet
    actual_delta = (samples[i] - samples[i-1]) & 0xFF  # 8-bit counter
    if actual_delta > expected_delta:
        dropped = actual_delta - expected_delta
        overruns.append((timestamps[i], dropped))
        print(f"Overrun at t={timestamps[i]:.3f}s: {dropped} packets dropped")

if not overruns:
    print("No DAQ overruns detected")
else:
    print(f"Total overruns: {len(overruns)} events")
    # Fix: reduce channel count, increase event period, or switch to XCP/ETH

Summary

DAQ lists are the core of XCP measurement: named groups of MEASUREMENT variables tied to an ECU event channel (OS task period). Each ODT maps to one DAQ packet transmitted by the ECU. DAQ overruns occur when the ECU cannot keep up with the configured sample rate — detected by sequence counter gaps in the MF4 recording and resolved by reducing channel count, increasing event period, or switching to XCP/ETH.

🔬 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.