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INCA Project Setup: Idle Speed Controller ECU

Setup StepINCA Menu / ActionVerification Check
Create experimentFile → New ExperimentEmpty experiment window opens
Import A2LFile → Add ECU Description → ECU_Engine_v2.3.a2lidle_setpoint (VALUE) and actual_idle_speed (MEASUREMENT) visible in browser
Configure hardwareHardware → Hardware Config → ES592 CAN, bit-rate 500 kbpsES592 shows green LED in hardware monitor
Set XCP IDsES592 settings → CRO ID 0x600, DTO ID 0x601Matches A2L IF_DATA XCP_ON_CAN values
ConnectDevice → Connect (F5)CONNECT response 0xFF in XCP Monitor; status bar shows CONNECTED
Verify A2LUpload idle_setpoint → expected 750 rpmDisplayed value matches known ECU default; if wrong check ECU_ADDRESS

Live Calibration: Idle Speed Setpoint

Pythonidle_cal_procedure.py
import inca_com as inca, time

inca.Connect("ECU_Engine_v2.3.a2l", channel="ES592_CAN1")

# Add measurements to DAQ
inca.AddMeasurement("actual_idle_speed", event="event_10ms")
inca.AddMeasurement("idle_controller_integrator", event="event_10ms")
inca.AddMeasurement("coolant_temp_degC", event="event_100ms")

inca.StartRecording("idle_cal_session_001.mf4")
inca.StartMeasurement()

# Step 1: check baseline
baseline = inca.GetCharacteristic("idle_setpoint")
print(f"Baseline idle_setpoint = {baseline} rpm")  # 750

# Step 2: raise setpoint to 800 rpm
inca.SetCharacteristic("idle_setpoint", 800.0)
time.sleep(3.0)  # wait for PID settle

actual = inca.GetMeasurementAverage("actual_idle_speed", window_ms=1000)
print(f"After 800 rpm setpoint: actual = {actual:.0f} rpm")

# Step 3: raise to 850 rpm
inca.SetCharacteristic("idle_setpoint", 850.0)
time.sleep(3.0)
actual = inca.GetMeasurementAverage("actual_idle_speed", window_ms=1000)
print(f"After 850 rpm setpoint: actual = {actual:.0f} rpm")

# Step 4: test COPY_CAL_PAGE (persist 850 rpm)
inca.CopyCalPage(source=0, dest=1)  # working → reference
print("Changes saved to Flash reference page")

inca.StopMeasurement()
inca.StopRecording()
inca.Disconnect()

CANape 3D Map Editor Exercise

CASLthrottle_map_exercise.casl
/* CANape exercise: observe active cells in throttle_torque_map during load sweep */

on start {
    Connect();
    StartMeasurement();

    /* Open 3D map window (done manually in GUI — cannot script window layout) */
    /* The map window shows throttle_torque_MAP with live active-cell highlight */

    /* Perform a slow throttle sweep to visit all map cells */
    Write("Performing throttle sweep — watch 3D map active cell tracking...");
    Wait(30000);  /* 30 second sweep controlled by dyno operator */

    /* After sweep: identify cells with zero visit count */
    /* These cells were never interpolated → may safely use estimated values */
    int visited = CountVisitedMapCells("throttle_torque_MAP");
    int total   = GetMapCellCount("throttle_torque_MAP");
    Write("Visited %d/%d map cells during sweep", visited, total);

    StopMeasurement();
    SaveMeasurement("throttle_map_sweep.mf4");
    Disconnect();
}

Session Documentation: INCA Change Log

Documentation ItemINCA SourceRequired For
Parameter change logAuto-generated: parameter name, old value, new value, timestamp, userCDM review; emissions homologation audit trail
Dataset snapshotDataset → Save As → 'idle_ramp_v2_validated'Reproducible baseline; CDM import
Diff vs baselineDataset → Compare → select baselineCalibration lead review sign-off
MF4 recordingAutomatic during sessionPost-session MDA analysis; homologation evidence archive
Shellexport_session_docs.sh
#!/bin/bash
# Post-session documentation export
inca_cli.exe export_changelog     --experiment "ECU_Engine_dev"     --from "2026-02-15 09:00"     --to   "2026-02-15 17:00"     --output "session_changelog_20260215.xlsx"

inca_cli.exe export_dataset     --dataset "idle_ramp_v2_validated"     --format DCM     --output "idle_ramp_v2_validated.dcm"

echo "Session documentation complete" 

Summary

The hands-on tool project walks the complete cycle: INCA project setup, XCP connection verification, DAQ measurement monitoring, live parameter edit with COPY_CAL_PAGE persistence, and session documentation export. The same workflow applies in CANape — the 3D Map Editor with active-cell tracking is CANape's most powerful live calibration feature. Always export the INCA change log before ending the session — it is the authoritative record of what was changed.

🔬 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

  1. 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'.
  2. 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.
  3. 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.
  4. 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.

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