Combine the speed of neural networks (ANNs) and the accuracy of finite element (FEM) for obtaining a versatile tool for inductor computation and optimization (buck, boost, resonant, filter, etc.)
Explore the trade-offs (power density, mass, losses, load profile, cost, etc.) with a graphical user interface and select the optimal design.
Get all the properties of a selected design down to the smallest detail (geometry, equivalent circuit, field, losses, temperature, etc.).
AI-mag was developed and brought to you by the Power Electronic Systems Laboratory at ETH Zurich. The source code and the data are under BSD license.
