Modeling and Analysis of Permanent Magnet Spherical Motors by a Multitask Gaussian Process Method and Finite Element Method for Output Torque

被引:16
作者
Wen, Yan [1 ,2 ,3 ]
Li, Guoli [2 ]
Wang, Qunjing [4 ]
Guo, Xiwen [2 ]
Cao, Wenping [2 ]
机构
[1] Anhui Univ, Sch Comp Sci & Technol, Hefei 230601, Peoples R China
[2] Anhui Univ, Sch Elect Engn & Automat, Hefei 230601, Peoples R China
[3] Anhui Univ, Natl Engn Lab Energy Saving Motor & Control Techn, Hefei 230601, Peoples R China
[4] Anhui Univ, Anhui Prov Lab Ind Energy Saving & Safety, Hefei 230601, Peoples R China
基金
中国国家自然科学基金;
关键词
Torque; Coils; Rotors; Permanent magnet motors; Gaussian processes; Permanent magnets; Induction motors; Multitask Gaussian process (MTGP); permanent magnet spherical motor (PMSM); torque calculation; DESIGN; ACTUATORS; MACHINE; FIELD;
D O I
10.1109/TIE.2020.3018078
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 precise position control applications. The control of these motors requires precise output torques by all coils at a specific rotor position, which is difficult to achieve in the three-dimension space. This article 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 three-dimensional problem with a reasonable computational accuracy and time. This article utilizes a data-driven method using only input and output data validated by experiments. The multitask Gaussian process 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.
引用
收藏
页码:8540 / 8549
页数:10
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