Andreas Rosskopf studied Applied Mathematics with a focus on Numerical Simulation in Erlangen, Germany. Afterwards he worked as a computational engineer in automotive, large drive and energy industries.
Since 2012, he has been working as a research associate in the department "Modeling and Artificial Intelligence" at Fraunhofer IISB in Erlangen and received his PhD in numerical methods for loss calculation of litz wires in 2018. In 2018, he founded the working group "AI-augmented Simulation “, and supports and initiates activities for data-driven design optimization of power electronic devices and systems. Since 2023 he's head of the "Modeling and Artificial Intelligence" department of the Fraunhofer IISB designing digital solutions in the field of power electronics, Technology Computer-Aided Design for semiconductor devices and lithography.
Based on a general overview of AI, we analyse current AI implementations and solutions in the application field of power electronics. We show how efficient algorithms on GPU hardware can accurately solve transient circuit simulations in fractions of a second and how ferrite losses can be estimated quickly and accurately using a data-based neural network. We provide insights into so-called Physics-Informed Neural Networks (PINNs), which combine physics, maths and AI to predict all relevant parameters of a transformer without simulation and measurement data, just using the corresponding fundamental physical equations.