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ASM Engine InCylinder Simulation

The ASM Diesel Engine InCylinder Simulation Package and the ASM Gasoline Engine InCylinder Simulation Package are open Simulink® models for developing and testing advanced electronic control units (ECUs) that support engine management based on in-cylinder pressure, variable valve timing, etc. They are fully integrated into the dSPACE tool chain and are typically used on a dSPACE Simulator for hardware-in-the-loop (HIL) testing of ECUs. They are complete and independent engine models that support all the relevant phases of the model-based development process, from early controller design to testing in the laboratory. Since the simulation packages are open Simulink models, users can simply add components or replace them with custom models to meet specific project requirements. The model parameters can be tuned even during online simulation. You will learn about the concept and the structure of the ASM engine in-cylinder simulation models. The course will also explain the basics of in-cylinder pressure-based engine simulation. Other items covered are engine model parameterization and model parameter optimization.

  • Engineers working on the HIL testing of ECUs in the area of advanced engine applications
  • Engineers who validate controller algorithm designs by doing offline simulation
  • Required: Previous experience with MATLAB® and Simulink®

  • Get an overview of the ASM engine in-cylinder simulation packages
  • Use the ASM engine in-cylinder model offline and on a dSPACE system
  • Parameterize the model
  • Optimize parameters

  • ASM Diesel Engine InCylinder Simulation Package
  • ASM Gasoline Engine InCylinder Simulation Package
  • MATLAB®/Simulink®
  • ModelDesk

  • Introduction to in-cylinder-pressure-based engine simulation
  • Introduction to the ASM Diesel Engine InCylinder Simulation Package and to the ASM Gasoline Engine InCylinder Simulation Package
  • Offline simulation with the model
  • Online simulation with the model on dSPACE hardware or VEOS
  • Handling with engine measurement data
  • Parameterizing the model
  • Optimizing model parameters

DatesLocation and time
On request
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