Real-Time Code Generation - HIL Testing

From Simulink Model to Real-Time Code

Code Generation Pipeline

  Simulink Model (.slx)
  +-- Fixed-step solver configured
  +-- I/O blocks inserted (dSPACE RTI or NI VeriStand blocks)
  +-- AUTOSAR SW-C or plain C target selected
       |
       v  [rtwbuild / Embedded Coder]
  Generated C code
  +-- model_step(): called every simulation tick
  +-- model_initialize(): called once at startup
  +-- rtwtypes.h: portable integer types
       |
       v  [Cross-compiler: GCC ARM / Intel x86 / QNX]
  Compiled shared library (.so / .dll)
       |
       v  [Platform deployment tool]
  Loaded onto real-time target
  Running at fixed step rate (e.g., 1 kHz)

  RTI (Real-Time Interface) for dSPACE:
  Inserts I/O blocks automatically from ConfigurationDesk mapping;
  generates .sdf (system description file) for ControlDesk variables

Embedded Coder Configuration for HIL

MATLABcodegen_config.m

% Configure Embedded Coder for HIL code generation
model = "VehicleDynamics_HIL";
cfg   = coder.config("dll");   % shared library for HIL platform

% Data types
cfg.DefaultUnderspecifiedDataType = "double";  % use double for HIL
cfg.PurelyIntegerCode = false;

% Optimisation
cfg.GenerateComments     = false;  % smaller binary
cfg.PreserveStaticInFcns = false;  % allow inlining

% Safety checks (keep for first HIL validation run)
cfg.RuntimeChecks = "off";   % disable after validated

% Model reference: sub-models compiled independently
% Allows parallel compilation of Engine, Brake, Dynamics models

% Build
codegen("-config", cfg, model);

% After build: measure execution time on target
% dSPACE: read DS_TASK_EXEC_TIME variable in ControlDesk
% Target: < 700 us for 1 ms step (70% utilisation)

SiL/PiL/HIL Consistency Verification

Check	Method	Tool	Acceptance Criterion
MiL vs SiL numeric equivalence	Run same scenario; compare signals	Simulink Test, MATLAB diff	Difference < floating-point epsilon (or justified
SiL vs PiL numeric equivalence	Run on target processor; compare output	Back-to-back test harness	Difference within compiler optimisation tolerance
PiL vs HIL timing	Measure task execution time on target	ControlDesk / VeriStand profiler	Execution time < 70% of step period (no overruns)
HIL vs vehicle validation	Run same manoeuvre; compare traces	MDF4 analysis tool	RMS error < 5% of signal range per model validation plan

Summary

Real-time code generation from Simulink is the bridge between control algorithm development and HIL testing. The generated model_step() function is called once per simulation tick - its execution time directly determines whether the HIL runs without overruns. Back-to-back testing (MiL vs SiL vs PiL vs HIL) at each step of the V-model confirms that compiler optimisations and floating-point differences between desktop and target processor do not introduce unexpected discrepancies in safety-critical outputs. ISO 26262 requires this equivalence to be demonstrated and documented when the HIL simulation environment is used as evidence in the safety case.

🔬 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.