Andreas Rosskopf studied Applied Mathematics with a focus on Numerical Simulation in Erlangen, Germany. Afterwards he worked as a computational engineer in the 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. Since 2018, he leads the working group "AI-augmented Simulation“, and supports and initiates activities for data-driven design optimization of power electronic devices and systems. His research covers Long-Short-term Memory (LSTM) for the prediction of batterie degeneration, Reinforcement Learning (RL) for the Optimization of electric circuits as well as varying applications of Physics Informed Neural Networks (PINN) for optics and power electronics.
Litz wires with several hundreds or even thousands of isolated strands are increasingly used in transformers, chokes, and inductive power transfer systems.
Tuesday 23 May 16:40 - 17:10 Central Stage
Material Innovation & Advancements- Magnets & Technology Applications
Litz wires with several hundreds or even thousands of isolated strands are increasingly used in transformers, chokes, and inductive power transfer systems.
Central Stage Europe/London