Abstract

Breakthrough innovations in electrical machines may be limited by parametric overlays and templates provided in commercial electromagnetic simulation software. Disruptive design spaces must therefore be explored using more flexible open-source software solutions. However, a significant scripting effort is necessary to define some new parametric geometries suitable for design optimization based on open source multiphysics solvers. This article illustrates the use of Pyleecan open-source simulation software under Python to more efficiently model, evaluate and optimize disruptive topologies of 2D or 3D electrical machines. The current status of Pyleecan initiative is first presented. Then, the principle and the advantages of the object-oriented approach of electrical machines are detailed. Some examples of complex innovative topologies that can be generated with Pyleecan are then introduced (e.g. complex winding, uneven slot types, multiple rotor and stators), as well as the optimization possibilities. Finally, the development roadmap of Pyleecan project is given.

Preprint

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