Konzeptentwicklung zur Prüfstandvernetzung
am Institut für Mechatronische Systeme im Maschinenbau
Advanced Design Project (ADP)
At the IMS, the potential for increasing the efficiency of powertrains by knowing the speed to be expected in the next few seconds is being investigated on the basis of AI-based predictions.
The Kolmogorov-Arnold networks (KAN) approach presented in April 2024 promises faster training, improved accuracy and interpretability compared to conventional multi-layer perceptrons (MLP). So far, only a simple Matlab implementation of KANs with basic functionality exists.
The aim of this advertised work is to realise a KAN implementation against the background of the Matlab Deep Learning Toolbox and to use it for speed prediction.
A data set comprising over 29,000 kilometres is available as a data basis.