Basics of ASCMO-MOCA

ETAS ASCMO-MOCA enables the optimization of model parameters and minimizes the deviation between model predictions and desired output values. ASCMO-MOCA is used for physics-based models, such as those found in ECUs and simulation environments, where generic models must be adapted to a specific engine, vehicle, or component using real measurement data, for example from an engine test bench or vehicle.

A common use case is the optimization of ECU models, such as virtual sensors for torque or exhaust-gas temperature. These models replace or monitor real sensors and are optimized to improve prediction quality by minimizing the deviation between the model prediction and real measurements across all measuring points. The parameters to be optimized can include maps, curves, and scalars.

ASCMO-MOCA supports various ways of working with models. Plant models and controller models can be loaded, connected, or modeled directly. The model can be represented as a set of formulas entered by the user, or existing models, for example from Simulink®, can be used. It is also possible to load measurement data, import and export model parameters, and define optimization tasks.

ASCMO-MOCA provides a wide range of functions and options for visualizing and analyzing both the data and the models used. Powerful algorithms can optimize a large number of free parameters simultaneously while considering constraints such as smoothness or monotonicity.

Another application is the optimization of emissions and fuel consumption for complex internal combustion engines in dynamic and transient driving cycles. This requires linking classic ASCMO data-based models to parts of the ECU software. Such linkages, as well as the joint optimization of different subcomponents, are straightforward in ASCMO-MOCA.

Since the methodology used in ASCMO-MOCA is not limited to internal combustion engines, the tool is also used in areas such as electric mobility, for example charging strategy, and component development.

In this chapter, the basic concepts of ASCMO-MOCA are described.

These are the following: