Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 29th June 2025, 01:37:10am CEST
Electromagnetic interference (EMI) is a significant challenge in power electronic systems, affecting their efficiency, reliability, and overall electromagnetic compatibility (EMC). Understanding EMI is therefore essential for designing robust and high-performance power electronic systems.
Despite its subtleness, EMC simulation has matured to provide significant contributions to the EMC design for power electronics.
This workshop provides a comprehensive overview of the EMC simulation of power electronic systems, covering circuit topologies, 3D modeling techniques, and recent progresses in the application of machine learning. Participants of the workshop will explore the challenges of modeling EMI in power electronics. The audience shall understand the goals and limits of different modeling approaches.
Demonstrations of modeling approaches using circuit and 3D simulation, as well as applying machine learning for multi-objective optimization will be given.
Presentations
4:20pm - 4:50pm
System Modeling at high (f > 30 MHz) frequencies
Jan Hansen1,2,3
1Institute of Electronics, Graz University of Technology, Austria; 2Christian Doppler Laboratory for EMC Aware Robust Electronic Systems, Austria; 3Silicon Austria Labs, Graz, Austria
This presentation focuses on system modeling for high-frequency EMI (f > 30 MHz), emphasizing the construction and simulation of 3D models. Additionally, this section covers the representation of assembly elements and subcomponents and discusses the accuracy and limitations of high-frequency modeling.
4:50pm - 5:50pm
Application of Machine Learning in EMC modeling
Patrick Dominik Gsoels1,2,3
1Silicon Austria Labs GmbH, Austria; 2Christian Doppler Laboratory for EMC Aware Robust Electronic Systems, Austria; 3Institute of Electronics, Graz University of Technology, Austria
This section explores the application of machine learning in EMC modeling. It presents techniques and examples of trained models. Additionally, it emphasizes the use of multi-objective optimization and other applications to improve EMI prediction and design efficiency.
