pypeec 4.6.0

PyPEEC - 3D PEEC Solver

PyPEEC - 3D PEEC Solver

• Website: pypeec.otvam.ch
• Repository: github.com/otvam/pypeec
• Package: pypi.org/project/pypeec

Summary

PyPEEC is a 3D quasi-magnetostatic PEEC solver developed at Dartmouth College within the Power Management Integration Center (PMIC). PyPEEC is a fast solver (FFT and GPU accelerated) that can simulate a large variety of magnetic components (inductors, transformers, chokes, IPT coils, busbars, etc.). The tool contains a mesher (STL, PNG, and GERBER formats), a solver (static and frequency domain), and advanced plotting capabilities. The code is written in Python and is fully open source!

Capabilities

PyPEEC features the following characteristics:

• PEEC method with FFT acceleration
• Representation of the geometry with 3D voxels
• Multithreading and GPU acceleration are available
• Fast with moderate memory requirements
• Import the geometry from STL, PNG, and GERBER files
• Draw the geometry with stacked 2D vector shapes or voxel indices
• Pure Python and open source implementation
• Can be used from the command line
• Can be used with Jupyter notebooks
• Advanced plotting capabilities

PyPEEC solves the following 3D quasi-magnetostatic problems:

• Frequency domain solution (DC and AC)
• Conductive and magnetic domains (ideal or lossy)
• Connection of current and voltage sources
• Extraction of the loss and energy densities
• Extraction of the current density, flux density, and potential
• Extraction of the terminal voltage, current, and power
• Computation of the free-space magnetic field

PyPEEC has the following limitations:

• No capacitive effects
• No dielectric domains
• No advanced boundaries conditions
• No model order reduction techniques
• Limited to voxel geometries

The PyPEEC package contains the following tools:

• mesher: create a 3D voxel structure from STL or PNG files
• viewer: visualization of the 3D voxel structure
• solver: solver for the magnetic field problem
• plotter: visualization of the problem solution

Project Links

• Website: https://pypeec.otvam.ch
• Repository: https://github.com/otvam/pypeec
• Releases: https://github.com/otvam/pypeec/releases
• Tags: https://github.com/otvam/pypeec/tags
• Issues: https://github.com/otvam/pypeec/issues
• PyPi: https://pypi.org/project/pypeec

Author

• Thomas Guillod
• Email: [e-mail]
• Website: https://otvam.ch

Credits

PyPEEC was created at Dartmouth College by the research group of Prof. Sullivan:

• Dartmouth College, NH, USA: https://dartmouth.edu
• Dartmouth Engineering: https://engineering.dartmouth.edu
• PMIC: https://pmic.engineering.dartmouth.edu

The FFT-accelerated PEEC method with voxels has been first described and implemented in:

• Torchio, R., IEEE TPEL, 10.1109/TPEL.2021.3092431, 2022
• Torchio, R., https://github.com/UniPD-DII-ETCOMP/FFT-PEEC

Copyright

(c) 2023 - Thomas Guillod - Dartmouth College

This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.