OPTIMUM DESIGN FOR IMPROVING MODULATING-EFFECT OF COAXIAL MAGNETIC GEAR USING RESPONSE SURFACE METHODOLOGY AND GENETIC ALGORITHM
Author(s) -
Linni Jian,
Guoqing Xu,
Jianjian Song,
Honghong Xue,
Dongfang Zhao,
Jianing Liang
Publication year - 2011
Publication title -
electromagnetic waves
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 89
eISSN - 1559-8985
pISSN - 1070-4698
DOI - 10.2528/pier11032316
Subject(s) - response surface methodology , coaxial , genetic algorithm , magnetic gear , computer science , materials science , algorithm , engineering , mechanical engineering , magnet , machine learning
Coaxial magnetic gear (CMG) is a non-contact device for torque transmission and speed variation which exhibits promising potential in several industrial applications, such as electric vehicles, wind power generation and vessel propulsion. CMG works lying on the modulating-effect aroused by the ferromagnetic segments. This paper investigates the optimum design for improving the modulating-effect. Firstly, the operating principle and the modulating-effect is analyzed by using 1-D field model, which demonstrates that the modulating- effect is essential for the torque transmission capacity of CMGs, and the shape of the ferromagnetic segments have impact on the modulating- effect. Secondly, the fitted model of the relationship between the maximum pull-out torque and the shape factors including radial height, outer-edge width-angle and inner-edge width-angle is built up by using surface response methodology. Moreover, FEM is engaged to evaluate its accuracy. Thirdly, the optimum shape of the ferromagnetic segment is obtained by using genetical algorithm.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom