Integration of data-based ETAS ASCMO models into a GT-POWER simulation
Simulation tools are widely used to reduce the amount of physical experimental tests during the design phase. By supplementing physically-based engine models with data-based models, the predictive accuracy can be improved significantly.
Function developers who use GT-Power plant models for function testing need extremely high accuracy of these models. They often find themselves going back to the test bench or the HiL system for validation. Or even worse, they have to wait for an available test bench or HiL system.
ETAS ASCMO is capable of generating high-accuracy models after a short time at the test bench to collect the data. By combining the physical GT-Power model with a data-based model generated by ETAS ASCMO the predictive efficiency of emissions simulations can significantly be improved. The reason for the improvement is ETAS ASCMO’s approach of using measurement data from the real system instead of predicting those values on the basis of a physical model.
Probably your DoE group already uses ETAS ASCMO and can provide the model for any function developer using GT-Power plant models.
By using a high-accuracy emissions model generated by ETAS ASCMO, you save schedule time and dyno costs. More function testing on the desktop or HIL changes function testing to a matter of minutes instead of days on the emissionstest bench.
* or other physical simulation models, e.g. AmeSim®, Simulation X