Modeling and Analysis of Permanent Magnet Spherical Motors by A Multi-task Gaussian Process Method and Finite Element Method for Output Torque

Abstract

Permanent magnet spherical motors (PMSMs) operate on the principle of the DC excitation of stator coils and three freedom of motion in the rotor. Each coil generates the torque in a specific direction, collectively they move the rotor to a direction of motion. Modeling and analysis of the output torque are of critical importance for in precise position control applications. The control of these motors requires precise output torques by all coils at a specific rotor position. It is difficult to achieve in the three-dimension space. This paper is the first to apply the Gaussian process to establish the relationship of the rotor position and the output torque for PMSMs. Traditional methods are difficult to resolve such a complex 3D problem with a reasonable computational accuracy and time. This paper utilizes a data-driven method using only input and output data validated by experiments. The multi-task Gaussian process (MTGP) is developed to calculate the total torque produced by multiple coils at the full operational range. The training data and test data are obtained by the finite element method. The effectiveness of the proposed method is validated and compared with existing data-driven approaches. The results exhibit superior performance of accuracy.

Publication DOI: https://doi.org/10.1109/TIE.2020.3018078
Divisions: Engineering & Applied Sciences > Electrical, Electronic & Power Engineering
Engineering & Applied Sciences > Power Electronics, Machines and Power System (PEMPS)
Engineering & Applied Sciences
Additional Information: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
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Related URLs: https://ieeexpl ... cument/9177338/ (Publisher URL)
PURE Output Type: Article
Published Date: 2020-08-25
Published Online Date: 2020-08-25
Accepted Date: 2020-08-06
Authors: Wen, Yan
Li, Guoli
Wang, Qunjing
Guo, Xiwen
Cao, Wenping ( 0000-0002-8133-3020)

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