Fraunhofer Institute for Integrated Systems and Device Technology IISBEnhancement of Simulation Methods by Artificial Intelligence and Machine Learning
The research group AI-augmented Simulation combines a wide range of physical-based simulation approaches and software tools with both mathematically advanced and efficient algorithms and AI frameworks to model and optimize power electronic devices and systems.
Simulation
■ Coupled electrical, thermal and mechanical simulations in the domain of micro- and power electronic devices and energy systems
■ Implementation of customized software packages to increase efficiency, performance and functionality of standard software products
■ Simulation of electrical components based on CAD data from 3D CT scans
Artificial Intelligence
■ Clustering unknown data sets using unsupervised learning algorithms
■ Recurrent neural networks for analyzing and predicting time series
■ Convolutional neural networks for signal and image processing
Optimization
■ Topology optimization of inductive components using gradient-based methods such as SIMP
■ Optimization of electrical networks and systems with genetic algorithms
■ Sensitivity analysis and visualization of big data