Journal
IEEE TRANSACTIONS ON MAGNETICS
Volume 55, Issue 6, Pages -Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMAG.2019.2899934
Keywords
Deep learning (DL); genetic algorithm (GA); inner permanent magnet (IPM) motor; multi-objective optimization; topology optimization
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This paper presents the fast topology optimization methods for rotating machines based on deep learning. The cross-sectional image of electric motors and their performances obtained during a multi-objective topology optimization based on the finite-element method and genetic algorithm (GA) is used for training of the convolutional neural network (CNN). Two different approaches are proposed: 1) CNN trained by preliminary optimization with a small population for GA is used for the main optimization with a large population and 2) CNN is used for screening of torque performances in the optimization with respect to the motor efficiency.
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