The ASCMO family consists of the base product ASCMO-DESK as well as the three main products ASCMO-STATIC, ASCMO-DYNAMIC, and ASCMO-MOCA. Add-ons allow the functionalities to be expanded for specific tasks. One of the benefits of this type of product model is that users are free to combine the various ASCMO products as they wish. Users therefore get exactly the functions they need for their specific area of work.
ETAS ASCMO-DESK is the base product of the ASCMO family and serves as the common starting interface for ASCMO-STATIC, ASCMO-DYNAMIC, and ASCMO-MOCA. It also includes useful tools for managing and calculating driving cycles, displaying scatter plots, and editing calibration data.
ETAS ASCMO-STATIC enables users to create data-based models that model the stationary behavior of complex systems. ASCMO-STATIC provides a wealth of functions and options for visualizing, analyzing, and optimizing the system behavior. It can also be used for creating experimental designs based on the DoE methodology (design of experiments).
ETAS ASCMO-DYNAMIC enables users to create data-based models that model the dynamic/transient behavior of complex systems. ASCMO-DYNAMIC provides a wealth of functions and options for visualizing and analyzingthe system behavior. It can also be used for creating experimental designs based on the DoE methodology (design of experiments).
ETAS ASCMO-MOCA facilitates the efficient optimization of parameters, such as characteristic maps and curves, in physics based models. These models can be entered into the tool as a formula or linked as a Simulink®, FMU, TSim Plugin, COSYM Simulation or ASCET model.
The functionalities of the main ASCMO products can be expanded for specific tasks using the add-ons listed below. These add-ons either supplement a particular product or supplement all of the products. The images shown beside each add-on indicate which ASCMO products it is compatible with.
ASCMO-GO (Global Optimization)
ASCMO-GO is an add-on that expands the optimization method integrated in ASCMO-STATIC, which takes into consideration the full (global) operating range of an engine during the optimization. This enables, for example, the direct optimization of cumulative emissions and fuel consumption while maintaining characteristic map smoothness and adhering to typical driving cycles.
ASCMO-MCI (Model Compression)
ASCMO-MCI enables users to create models with significantly reduced complexity in terms of memory requirements and computing time. Its functionality includes an advanced compression algorithm that reduces the number of basic functions needed for the desired model accuracy. It furthermore includes a module for “symbolic regression”. This provides a special way of identifying functional correlations between inputs and outputs of a given system. Since the resulting model contains only simple mathematical operations, it is usually uncomplicated and efficient and can most likely be executed on a real-time critical system. In addition, these models are typically physically interpretable, thus making it possible to also use the highly accurate ASCMO models in real-time critical environments like ECUs.
ASCMO-ME (Model Export)
ASCMO-ODCM (Online DoE)
ASCMO-ODCM helps, for example, to reduce the risk of engine or test bench problems occurring with a new, unfamiliar engine during a DoE measurement. After each new measurement, ODCM uses the feedback regarding engine running stability and limit violations to iteratively and intelligently adapt the DoE test run. ODCM contains the logic component – test bench automation is necessary to carry out the measurements.
ASCMO-SDK (Software Development Kit)
ASCMO-SDK provides a MATLAB® interface to ASCMO. This allows ASCMO to be controlled remotely via a command line as well as via scripts, and it allows user-defined functionalities to be integrated into the ASCMO environment. These can be, for example, any kind of visualization or data processing or even modeling and optimization algorithms. Moreover, this interface can be used to establish a connection to test bench automations.
ASCMO-SIG (Signal Trace Modeling)
ASCMO-SIG enables users to create signal curve models, such as cylinder pressure curves based on static inputs. The dependencies of the signal curves on the input parameters can be visualized and optimized with respect to a target curve.