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