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Our engineering team partnered with a global mobility technology leader specializing in advanced solutions for the automotive industry to address the costly and time-consuming limitations of embedded software development. By creating a scalable Virtual ECU (Electronic Control Unit) simulation environment, we enabled early software validation, automated testing, and seamless integration into CI/CD pipelines. This approach accelerated time-to-market, reduced reliance on physical prototypes, and delivered higher-quality, compliant embedded software for complex EV systems.

Business Goals

The client is a top-tier integrated mobility technology provider, delivering advanced solutions in connectivity, autonomous driving, shared mobility, and electrification (CASE) with a global footprint across 20+ countries. To support innovation at this scale, rapid prototyping and validation of complex ECUs are critical. However, their over-reliance on physical ECU prototypes created major barriers in their product development lifecycle, resulting in prototyping delays, limited testing flexibility, and rising hardware costs. Additionally, inadequate early validation increased system downtime, raised maintenance costs, and posed risks of product recalls and compliance failures.

The organization needed a solution that could:

  • Accelerate development cycles by enabling early software validation and reducing dependency on physical ECU prototypes.
  • Minimize testing effort by automating simulation and integrating embedded software into CI/CD pipelines.
  • Improve reliability of software validation with stable, automated simulation environments that replicate real ECU behaviour.
  • Enhance scalability by supporting parallel testing as EV platforms grow in complexity.

Solution

We built a Virtual ECU simulation platform that removed the bottlenecks of hardware-dependent testing and enabled rapid, scalable, and automated validation of embedded software.

Before Implementation:

  • Prolonged release cycles due to dependency on physical prototypes.
  • High R&D costs tied to hardware procurement and lab resources.
  • Limited debugging and validation capability before hardware availability.
  • Restricted scalability for parallel development streams.
  • Ongoing compliance risks due to insufficient early-stage software testing.

After Implementation:

  • Embedded software validation began early in the lifecycle, significantly accelerating release timelines.
  • Hardware costs were reduced by replacing prototypes with virtual simulations.
  • Continuous, automated simulation improved testing accuracy and reduced defects.
  • Scalable workflows supported parallel development and CI/CD automation.
  • Advanced debugging and validation ensured compliance and safety before deployment.

Key Highlights

Virtual ECU Creation & Simulation

  • Converted embedded software into a Virtual ECU executable compatible with Linux and Windows environments.
  • Enabled early development, debugging, and validation without reliance on hardware prototypes.

Plant Model Integration

  • Integrated the Virtual ECU with Model-in-the-Loop (MIL) plant models to simulate powertrain and vehicle dynamics.
  • Applied inverse transform modeling for realistic signal interaction and control feedback.

Advanced Virtualization & Automation

  • Co-simulation of the Virtual ECU and plant models executed as DLLs on virtualization tools (e.g., Synopsys Silver, dSPACE VEOS).
  • Automated execution enabled via APIs and command-line tools, with full data logging of signals and events.

Robust Validation & Debugging

  • Virtual ECU outputs validated against both MIL simulations and real ECU runs.
  • Early-stage debugging caught defects before hardware testing, reducing downstream failures.

CI/CD Pipeline Integration

  • Seamlessly embedded into CI/CD workflows with automated builds, regression testing, and parallel simulations.
  • Removed hardware bottlenecks, accelerating development while improving software quality and compliance.

Outcomes

  • Accelerated Release Cycles with Early-Stage Software Validation
  • 40% Reduction in Hardware Prototype Costs
  • 30–40% Faster Root Cause Analysis through Advanced Debugging
  • Automated Scalability with CI/CD-Driven Continuous Testing
  • Enhanced Compliance and Risk Mitigation through Thorough Virtual Validation

Technologies Used

  • Virtualization Tools: Synopsys Silver, ETAS ISOLAR-EVE, dSPACE VEOS, Vector vVIRTUALtarget
  • Modeling Tools: MATLAB, Simulink, Stateflow, Fixed-Point Designer
  • System-Specific Tools: Powertrain block set, Simscape
  • Programming & Automation: Python, PowerShell, Batch, VBA
  • Build Tools: CMake, Ninja, Visual Studio