Abstract
PurposeThe purpose of this paper is to develop a novel optimization method that can improve the convergence of the multi-material topology.Design/methodology/approachIn the proposed method, the optimization procedure is divided into two steps. In the first step, a global search is performed to probabilistically determine the material distribution of multi-segmented magnets. In the second step, the design area is limited and a local search is performed to determine the detailed magnet shape.FindingsBecause the first optimization step determines the arrangement of the magnetization vectors according to the rotational position, as in a d-axis flux concentration orientation, the optimal solution can be obtained with a smaller volume of magnets than the conventional method.Research limitations/implicationsBecause a few case studies are considered in this paper, additional verification is required, such as application to different types of motors, to clarify scalability.Practical implicationsThe solution obtained using the proposed method has a smaller amount of magnet than the solution obtained using the conventional method and can fully satisfy the average torque constraint.Originality/valueThe proposed method differs from the conventional method in that the material distribution is determined according to the probability function in the first optimization step.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: COMPEL - The international journal for computation and mathematics in electrical and electronic engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.