ETAS ASCMO is the easy-to-use-solution for advanced model-based calibration and data-based modeling in significantly less time.
ETAS ASCMO enables the fast and efficient development of accurate data-based models. Once created, these high-accuracy models can be used to optimize parameters of real systems such as engine ECUs or plant models in different simulation environments (e.g. Simulink or HiL-Systems). Both, steady state and dynamic/transient system behaviors can be captured.
The effort to create data (measured or simulated) for the real system can be significantly reduced by using the DoE (Design of Experiments) approach. Traditionally, using DoE to determine the minimal number of necessary measured data points is difficult. ETAS ASCMO makes it easy. High-accuracy models are generated automatically by using modern statistical learning processes (Gaussian processes). Even highly complex system behaviors can be described without the prior need for detailed system knowledge or special mathematical expertise in the used algorithm. ETAS ASCMO offers a wide range of functions for a huge number of use cases (i.e. visualization, model evaluation) as well as various powerful optimization algorithms.
So why use ETAS ASCMO?
Because it enables even non-modeling experts to generate high-accuracy models clearly faster!
Main uses for ETAS ASCMO:
- Efficient calibration of diesel- and gasoline engines
- Model-based fuel and emissions optimization
- Controller calibration (e.g. drivability, boost-pressure, idle)
- Complex function parameterization (e.g. air charge, torque structure)
- Optimization of valves, sensors and other hardware components
- Acceleration of calculation time for physically-based simulations
- Improved accuracy of physically based simulations
- Efficient model-based controller layout and calibration with transient models
- Creation of high-accuracy dynamic models
- Optimization and calibration of many other technical systems such as batteries, gear boxes, hydraulic pump units, electric engines, …