Thorsten Huber

After studying mechanical engineering at the University of Erlangen-Nuremberg, Thorsten worked in different divisions of the Bosch Group: first in the area of injection system development at the Robert Bosch; afterward as commercial vehicle calibrator at Bosch Engineering. In both positions, he focused on test bench automation, model-based calibration and tool development. Since 2012, he has been a senior product and solution manager at the ETAS, responsible for the areas of data-based AI modeling, model-based calibration and data analytics.

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Presentation

Enhancing test bench efficiency with real-time connection and self-learning AI

This talk showcases the benefits of combining fast ECU access with self-learning AI methods. Automated self-learning of meaningful ranges for parameter variations helps improve the efficiency of test runs, while fast variation of parameters and instant reaction to limit violations improves stability and security at the benches. Combining both methods by flexible automation increases the benefits even more.