Virtual ECUs and SIL Simulation: Accelerating Software-defined Vehicle Development with MATLAB & Simulink

As the automotive industry transitions toward software-defined vehicles (SDVs), software complexity is increasing at a rate faster than traditional development processes can keep up with. OEMs and Tier-1 suppliers must integrate, validate, and deploy electronic control unit (ECU) software earlier and more frequently, often before physical hardware is available. This shift raises a critical question: How can engineering teams ensure software quality, system integration, and functional safety without hampering innovation?

Virtual electronic control units (vECUs) and software-in-the loop (SIL) simulation provide a solid response to the challenge. By enabling production ECU software to run in a virtual environment, teams can validate functionality, integration, and performance much earlier in the V-model. This article builds on our previous insights into software-defined vehicles and focuses on how MATLAB® and Simulink® support Virtual ECU workflows as a core enabler of SDV development.

What are Virtual ECUs and SIL Simulation? 

A virtual electronic control unit (vECU) is a software-based representation of an automotive ECU that runs production code on a PC or virtual platform. Combined with software-in-the-loop (SIL) simulation, engineers can execute, test, and debug ECU software together with plant models, communication stacks, and system-level simulations without relying on physical hardware.

Using MATLAB and Simulink, development teams can run the same code that will later execute on the target ECU, to ensure consistency across SIL, processor-in-the-loop (PIL), hardware-in-the-loop (HIL), and vehicle testing. This approach enables early verification of functional behavior, timing, and interfaces while maintaining full traceability across the development lifecycle.

Use Cases of Virtual ECUs in Software-defined Vehicles 

Virtual ECUs support a broad range of SDV workflows, from early development to validation and continuous integration. The following high value use cases illustrate how vECU and SIL simulation help engineering teams accelerate development while reducing integration risks.

• Early development without hardware: 
  Virtual ECUs enable engineering teams to run production ECU software on a virtual platform before silicon or target hardware becomes available. This is especially critical in SDV programs where software and hardware development unfold in parallel. Early execution helps to identify architectural, timing, and resource-related issues long before physical ECUs are introduced.

• Virtual software integration testing:
  Software components can be integrated and tested virtually, including AUTOSAR Runtime Environment (RTE) interfaces, middleware communication, and inter-ECU signals. This allows teams to detect interface mismatches and communication issues early on. As SDV architectures scale, early integration testing becomes essential to avoid costly late-stage failures.

• Virtual calibration:
  Virtual ECU environments support desktop-based calibration and tuning for powertrain, battery management systems (BMS), ADAS, and automated driving functions. Engineers can iterate rapidly without relying on limited test benches or prototype vehicles. This accelerates optimization cycles while maintaining traceability between calibration parameters and system behavior.

• Continuous integration (CI) and non-regression testing:
  Virtual ECUs integrate seamlessly into continuous integration (CI) pipelines, which enable automated SIL-based tests after every code change. This ensures that new software updates do not introduce errors to the codebase. For SDV programs with frequent software releases, CI-driven SIL testing is key to maintaining quality and stability.

• End-to-end feature validation:
  Multiple virtual ECUs can be co-simulated within a virtual vehicle network to validate complete features end to end. For example, ADAS workflows—from perception to sensor fusion to actuation—can be tested in a closed-loop environment. This system-level validation ensures that individual ECU functions work together as intended.
• Virtual robustness testing:
  Virtual environments allow teams to systematically inject faults such as sensor failures, communication dropouts, or power-cycle events at scale. These tests can be automated and repeated without risking hardware damage. Robustness testing is especially important for safety-critical SDV functions and rare edge cases.

How MATLAB & Simulink Enable Virtual ECU Workflows 

Virtual ECU workflows can be divided into two main categories: 1) virtual ECU creation, and 2) virtual ECU integration. MATLAB and Simulink support both workflows, though each requires a different approach.

Virtual ECU Creation 

This workflow focuses on creating a virtual representation of the ECU hardware. MathWorks’ Functional Mock-up Interface (FMI) support enables you to export Simulink models as functional mock-up units (FMUs), which can be used as initial vECU models. This approach allows you to build standardized virtual ECU components
that are interoperable across various simulation environments.

Virtual ECU Integration 

In the Virtual ECU integration workflow, Simulink serves as both a development and integration platform. You can develop embedded software in Simulink and generate hardware-specific code from your designs using automatic code generation tools. The generated vECU code runs in a third-party vECU environment, while Simulink acts as the integration platform. This enables you to interface with the vECU software directly from Simulink and integrate it with physical plant models, creating a setup that closely resembles a virtual hardware-in-the-loop (HIL) system for comprehensive testing and validation.

Essential Products for Virtual ECU & SIL

All products mentioned are developed by MathWorks®

• MATLAB® – Algorithm development, data analysis, and automation

• Simulink® – Model-based design and system-level simulation

• Embedded Coder™ – Production C/C++ code generation for ECUs

• Simulink Compiler – FMU generation for vECUs
• SciEngineer Professional Services – SDV consulting, workflow design, and toolchain integration

Summary 

Virtual ECUs and software-in-the-loop simulation have become foundational technologies for software-defined vehicle development. By enabling early validation, scalable testing, and continuous integration–driven workflows, they help OEMs and Tier-1 suppliers reduce integration risks while accelerating software delivery.

By combining MATLAB and Simulink with model-based design and virtual testing, engineering teams gain the flexibility needed to decouple software development from hardware availability: one of the core principles of the SDV paradigm. At SciEngineer, we support automotive teams with proven tools and deep engineering expertise to help them scale SDV programs with confidence.

Learn More about Software-defined Vehicles 

• The Road to Software-defined Vehicles: From Vision to Implementation 
• Software-defined Vehicles: The New Era of the Automotive Industry 

FAQ: Virtual ECU and SIL 

What is the difference between Virtual ECU and HIL testing? 
Virtual ECU and SIL testing run production ECU software on a PC or virtual platform for early validation before hardware is available. Hardware-in-the-loop (HIL) testing adds real ECU hardware and real-time simulation and is typically used in later development stages.

How does SIL testing support software-defined vehicle development? 
SIL testing allows teams to execute production C/C++ code together with plant models in Simulink, making it ideal for continuous integration, regression testing, and early system-level validation in SDV programs.

When should engineering teams use virtual ECUs?
Virtual ECUs can be used from early algorithm development through continuous integration and system validation, well before HIL and vehicle testing, to detect issues early and reduce development risk.