2011
DOI: 10.2528/pier11032316
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Optimum Design for Improving Modulating-Effect of Coaxial Magnetic Gear Using Response Surface Methodology and Genetic Algorithm

Abstract: Abstract-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 demo… Show more

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Cited by 32 publications
(20 citation statements)
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“…Therefore global optimization methods are a good option and can be used for auxiliary design. In recent years, many evolutionary algorithms have been proposed for solving design problems in electromagnetics such as differential evolution (DE) [16], particle swarm optimization (PSO) [12,[17][18][19] and genetic algorithm (GA) [20][21][22][23]. Among them, the PSO [12,17,18] and the GA [23] have already been used in power divider designs.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore global optimization methods are a good option and can be used for auxiliary design. In recent years, many evolutionary algorithms have been proposed for solving design problems in electromagnetics such as differential evolution (DE) [16], particle swarm optimization (PSO) [12,[17][18][19] and genetic algorithm (GA) [20][21][22][23]. Among them, the PSO [12,17,18] and the GA [23] have already been used in power divider designs.…”
Section: Introductionmentioning
confidence: 99%
“…A key issue in genetic algorithm programming is the selection of a fitness function for obtaining the best solution to a problem [28]. An inappropriate fitness function may lead to the wrong answer.…”
Section: Fitness Functionmentioning
confidence: 99%
“…Thin parallel wires minimize the skin effect; therefore it is not considered in Equation (28). Coil length and end-winding length are l and l e , respectively.…”
Section: Finite Volume Analysis (Fva)mentioning
confidence: 99%
“…In recent years, several evolutionary algorithms have emerged for solving design problems in electromagnetics such as genetic algorithm (GA) [1][2][3][4][5], micro-genetic algorithm (MGA) [6,7], particle swarm optimization (PSO) [8][9][10][11] and differential evolution strategy (DES) [12][13][14][15][16].…”
Section: Introductionmentioning
confidence: 99%