About ETAS ASCMO

ASCMO (Advanced Simulation for Calibration, Modeling and Optimization) is a tool for modeling the input/output behavior of unknown systems based on measuring data obtained using methods of the design of experiments.

This data-based modeling is necessary and successful when a precise physical description of the system is not possible. The high model quality that can be achieved allows for mapping even complex relationships, such as the global behavior of an internal combustion engine.

After modeling, ETAS ASCMO offers a variety of possibilities for visualizing the system behavior and for calibration/optimization based on models. The focal point of the calibration is the modeling and optimization of the "internal combustion engine" system in support of the calibration.

However, the modeling and optimization methods can also be applied to any other systems in which the output variables are differentiably dependent on the input variables.

Design of Experiments (DoE)

Design of experiments is a method for data-based modeling of unknown systems.

The process begins with an experiment plan to obtain data for model training using minimal measuring effort. This dataset is then used to train the model.

The models are based on mathematical approximation methods and are capable of reproducing the behavior of the measured system.

The goal of the modeling is to evaluate and optimize the system's behavior, such as determining the input variables that lead to optimal output variables (maximum performance, minimum consumption/emission) for an internal combustion engine.