Multiobjective optimization method based on a genetic algorithm for switched reluctance motor design

Mirzaeian, B.; Moallem, Mehdi; Tahani, V.; Lucas, Caro

doi:10.1109/20.999126

Cited by 97 publications

(42 citation statements)

References 11 publications

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“…In [9], the augmented Lagrangian method was used to determine optimum magnetic circuit parameters to minimize torque ripple. In [10], high efficiency and low torque ripple were investigated using a genetic fuzzy algorithm.…”

Section: Introductionmentioning

confidence: 99%

Optimization design of a doubly salient 8/6 SRM based on three computational intelligence methods

Rebahi¹,

Bentounsi²,

Bouchekara³

et al. 2016

Turk J Elec Eng & Comp Sci

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Abstract:The aim of this paper is to optimize an 8/6 doubly salient switched reluctance machine using three computational intelligence methods, which include particle swarm optimization, a genetic algorithm, and differential evolution.Three cases are investigated where different parameters are considered like the stator pole arc, rotor pole arc, and ratios, which define the stator yoke and rotor thickness. The objective functions considered are the average torque and the torque-to-weight functions. The simulations are carried out using MATLAB and FEMM software. The optimal results found are compared with the initial design, and it is shown that high improvements are achieved.

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Section: Introductionmentioning

confidence: 99%

Optimization design of a doubly salient 8/6 SRM based on three computational intelligence methods

Rebahi¹,

Bentounsi²,

Bouchekara³

et al. 2016

Turk J Elec Eng & Comp Sci

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show abstract

“…To select the fitness function, other parameters, too, should be considered: number of population, chromosome representation, mutation, and crossover. Another possible problem arises when one of the genes created is rather better than the other genes [33]; the answer may go towards the local solution. This is overcome by selecting a large number of populations.…”

Section: Genetic Algorithm and Optimizationmentioning

confidence: 99%

Genetic Algorithm and Finite Element Analysis for Optimum Design of Slotted Torus Axial-Flux Permanent-Magnet Brushless Dc Motor

Mahmoudi¹,

Rahim²,

Ping³

2011

PIER B

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Abstract-This paper presents an inside-out axial-flux permanentmagnet brushless DC motor optimized by Finite Element Analysis (FEA) and Genetic Algorithm (GA) that uses sizing equation. The double-sided slotted-stator designed TORUS motor has sinusoidal back EMF waveform and maximum power density. The GA obtained the dimensions that gave the motor its highest power density. Field analysis of the dimensions was then put through FEA, to obtain and re-optimize the motor's characteristics. Possible design parameters were investigated via use of Commercial Vector Field Opera 14.0 software used in three-dimensional FEA simulation and of MATLAB 2010a in GA programming. Techniques such as modifying winding configuration and skewing the permanent magnets were explored to achieve the most-sinusoidal back-EMF waveform and minimized cogging torque. The desired technical specifications were matched by simulation results of the 3D FEA and the GA. The FEA and the GA simulation results comparison of the flux density in different parts of the designed motor at no-load condition agreed well.

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“…Three dimensional FE analysis is still time consuming although computer performance has been significantly improving. In particular, heavy computational burden in the three dimensional FE analysis causes serious problems when it is applied to optimizations [1][2][3]. It is, therefore, strongly required that the computational time for the FE analysis is reduced.…”

Section: Introductionmentioning

confidence: 99%

Model Reduction of Three-Dimensional Eddy Current Problems Based on the Method of Snapshots

Sato

Igarashi

2013

IEEE Trans. Magn.

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The model reduction based on the method of snapshots is applied to the finite element analysis of three dimensional transient eddy current problems. It is known that accuracy of the reduced model highly depends on the number of snapshots. In this paper, we introduce a novel method which determines the adequate number of snapshots automatically. It is shown that the computational time can be reduced when using the model reduction based on the present method.Index Terms-Model order reduction, method of snapshots, proper orthogonal decomposition, finite element method, eddy current problem.

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Multiobjective optimization method based on a genetic algorithm for switched reluctance motor design

Cited by 97 publications

References 11 publications

Optimization design of a doubly salient 8/6 SRM based on three computational intelligence methods

Optimization design of a doubly salient 8/6 SRM based on three computational intelligence methods

Genetic Algorithm and Finite Element Analysis for Optimum Design of Slotted Torus Axial-Flux Permanent-Magnet Brushless Dc Motor

Model Reduction of Three-Dimensional Eddy Current Problems Based on the Method of Snapshots

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