KITE

AI-basedtopology optimization ofelectricalmachines - KITE.

The increasing market penetration of electromobility and the resulting growth in unit numbers mean that the material requirements for central components in electrical machines, such as magnets, and the energy efficiency of electrical machines are becoming critical both economically and ecologically, and the ability to optimize these is proving to be highly relevant to competition.

The aim of the KITE joint project is to develop highly efficient motor topologies for electric drive machines. This will be helped by an artificial intelligence (AI)-based model that maps the large solution space of possible topologies and proposes new highly efficient topologies. On the one hand, the project aims to substantially accelerate the development process by efficiently evaluating a large number of possible topologies with regard to various quality criteria in an early development phase. On the other hand, the design itself is to be supported by AI methods.

At the beginning of the project, requirements are first analyzed and specifications are defined in order to establish a concept for the development of the electric drive machines. Next development steps will include AI modeling, database expansion, and building the intelligent tool chain. One of the main works will be the training of the topology optimization algorithm. The project will be completed by the prototypical implementation of different prime movers and their testing on engine test benches.

Project duration: 01.09.2021 to 31.08.2024

• Volkswagen AG
• Merantix Labs GmbH
• FG Intelligent Embedded Systems, Prof. Dr. rer. nat. Bernhard Sick, University of Kassel
• Department of Vehicle Systems and Fundamentals of Electrical Engineering, Prof. Dr. rer. nat. Ludwig Brabetz, University of Kassel

Based on a resolution
of the German Bundestag