ASCMO – Data-based modeling and model-based calibration

The ETAS ASCMO product family offers a wide range of solutions for data-based system modeling and optimization.

ASCMO stands for Advanced Simulation for Calibration, Modeling, and Optimization.

By using advanced AI methods from the field of machine learning, it is possible to accurately model as well as analyze and optimize the behavior of complex systems on the basis of a small set of measurement data.

Areas of use

Typical applications are in model-based/virtual ECU calibration:

  • Prediction of fuel consumption and emissions for internal combustion engines and the optimization of the relevant ECU parameters in this context
  • Calibration of the parameters of complex ECU functions, such as physics based models (virtual sensors)
  • The data-based plant models created with ETAS ASCMO are also integrated into real-time critical systems, such as series-production ECUs
  • ETAS ASCMO is furthermore deployed in areas such as function development, system design, component development, and process optimization in production


  • Easy to use with no specialized knowledge required
  • Powerful AI methods from the field of machine learning
  • Interactive graphical representation of multidimensional dependencies
  • Ability to share models and data using standardized formats
  • Powerful MATLAB® and COM interfaces for integrating customer-specific functions and tools as well as for linking to test-bench automations