Multi-objective optimization of a magnetically levitated planar motor with multi-layer windings

Guo, Liang, Zhang, He, Galea, Michael, Li, Jing and Gerada, C. (2016) Multi-objective optimization of a magnetically levitated planar motor with multi-layer windings. IEEE Transactions on Industrial Electronics, 63 (6). pp. 3522-3532. ISSN 0278-0046

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Abstract

In this paper, a novel magnetically levitated coreless planar motor with three-layer orthogonal overlapping windings is shown to have higher power density and higher space utilization compared to other coreless planar motors. In order to achieve maximum forces with minimum cost and minimum space, a multi-objective optimization of the novel planar motor is carried out. In order to reduce the computational resources required for finite element analyses, a fast but accurate analytical tool is developed, based on expressions of the flux density of the permanent magnet array, which are derived from the scalar magnetic potential method. The validity and accuracy is verified by 3D FE results. Based on the force formulas and the multi-objective function derived from the analytical models, a particle swarm optimization (PSO) algorithm is applied to optimize the dimensions of the planar motor. The design and optimization of the planar motor is validated with experimental results, measured on a built prototype, thus proving the validity of the analytical tools.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/790534
Additional Information: 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works
Keywords: Analytical modeling, planar motor, overlapping windings, multi-objective optimization
Schools/Departments: University of Nottingham, UK > Faculty of Engineering > Department of Electrical and Electronic Engineering
Identification Number: 10.1109/TIE.2016.2522389
Depositing User: Burns, Rebecca
Date Deposited: 29 Jun 2016 14:10
Last Modified: 04 May 2020 17:52
URI: https://eprints.nottingham.ac.uk/id/eprint/34476

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