AI-mag is a MATLAB toolbox (using also COMSOL and Python) for power electronic inductor optimization.
The goal of this tool is to combine the accuracy of the Finite Element Method (FEM) with the evaluation speed of Artificial Neural Network (ANN).
More precisely, the following workflow is implemented:
* Simulating many designs with FEM thermal and magnetic simulations (COMSOL)
* Extracting the important figures of merit out of the FEM simulations
* Extracting the same figures of merit with a simplified analytical model (for comparison)
* Training regression ANNs to reproduce the figures of merit (MATLAB or Python Keras and TensorFlow)
* Using the ANNs, quickly generate accurate inductor designs (without solving any FEM model)
* Multi-objective data exploration with a GUI
The following performances are achieved:
* The average error between the FEM simulations and the ANN predictions is below 1%
* The worst-case error between the FEM simulations and the ANN predictions is below 3%
* The tool is able generate 300'000 designs per second on a laptop computer
* The tool is able for compute 50'000 operating points per second on a laptop computer
This tool is developed by the Power Electronic Systems Laboratory at ETH Zurich and is available under the BSD License. The code is also available on the ETH Data Archive.
Thomas Guillod (2021). AI-mag (https://github.com/ethz-pes/AI-mag/releases/tag/v4.0), GitHub. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
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