Topology Optimization of Electric Motor Using Topological Derivative for Nonlinear Magnetostatics

We aim at finding an optimal design for an interior permanent magnet electric motor by means of a sensitivity-based topology optimization method. The gradient-based ON/OFF method has been successfully applied to optimization problems of this form. We show that this method can be improved by consider...

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Bibliographic Details
Published in:IEEE transactions on magnetics 2016-03, Vol.52 (3), p.1-4
Main Authors: Gangl, Peter, Amstutz, Samuel, Langer, Ulrich
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Derivatives
design optimization
Electric motors
Finite element analysis
Magnetic domains
Magnetism
Mathematical analysis
Mathematical models
Mathematics
Motors
Nonlinearity
Optimization
Optimization and Control
Partial differential equations
permanent magnet motors
Permanent magnets
rotating machines
Sensitivity
sensitivity analysis
Topology
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Summary:We aim at finding an optimal design for an interior permanent magnet electric motor by means of a sensitivity-based topology optimization method. The gradient-based ON/OFF method has been successfully applied to optimization problems of this form. We show that this method can be improved by considering the mathematical concept of topological derivatives (TDs). TDs for optimization problems constrained by linear partial differential equations (PDEs) are well understood, whereas little is known about TDs in combination with nonlinear PDE constraints. We derive the TD for an optimization problem constrained by the equation of nonlinear 2-D magnetostatics, illustrate its advantages over the sensitivities used in the ON/OFF method, and show numerical results for the optimization of an interior permanent magnet electric motor obtained by a level-set algorithm, which is based on the TD.
ISSN:0018-9464
1941-0069
DOI:10.1109/TMAG.2015.2496172