Hybrid Optimization Strategy using Response Surface Methodology and Genetic Algorithm for reducing Cogging Torque of SPM

Kim, Minjae; Lim, Jaewon; Seo, Jang-Ho; Jung, Hyun–Kyo

doi:10.5370/jeet.2011.6.2.202

Cited by 16 publications

(10 citation statements)

References 3 publications

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“…Despite its successful use in various processes, RSM has some limitations like, in case of more than six or seven variables, the number of variables interaction terms will increase and resulted in complexity of the study and the practical feasibility of the method will challenged [ 8 ]. In addition, the RSM fails to precisely describe an object function [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

Pathak¹,

Singh²,

Niwas³

et al. 2015

PLoS ONE

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Cholesterol oxidase (COD) is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD) and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO4, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL) obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500.

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Section: Introductionmentioning

confidence: 99%

Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

Pathak¹,

Singh²,

Niwas³

et al. 2015

PLoS ONE

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“…The process of Taguchi method, composed of OA with inner and outer array and the concept of quality loss, is described in more detail in the next section. 4 Taguchi method…”

Section: Reliability Examination Using Experimentsmentioning

confidence: 99%

“…Interior permanent magnet synchronous motors (IPMSMs) are widely used in home application, industrial, and electric and hybrid vehicle propulsion, because of their high efficiency, high torque density and wide speed range [1][2][3][4][5][6][7]. However, even though the electric motor is designed using finite element analysis (FEA) [8], its performance is not satisfactory in certain cases [9].…”

Section: Introductionmentioning

confidence: 99%

Optimal design of interior permanent magnet synchronous motor considering the manufacturing tolerances using Taguchi robust design

Kim¹,

Cho²,

Jang³

et al. 2014

IET Electric Power Applications

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The manufacturing tolerance of the permanent magnets (PMs) is inherent in the produce of the machine. These tolerances influence back electromotive force (EMF), which is an important response of the motor. In order to enhance the quality of the product, the authors need to reduce these tolerances, but it is very difficult and involves a number of costs. Therefore, this study presents a robust design of the EMF characteristic analysis considering the manufacturing tolerances of PM in the interior PM synchronous motor (IPMSM). Among the robust optimisation method, Taguchi robust design based on orthogonal array was applied. Finally, the validity of the analysis result is verified by comparing the optimum design model with present design model (mass production model) ones.

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“…Ecosystem-inspired optimizations have been widely used for the optimization of the electromagnetic machine [4][5][6][7][8][9][10][11][12][13][14][15]. These algorithms can find a number of optima, which include the global solution through a large number of function evaluations.…”

Section: Introductionmentioning

confidence: 99%

“…For these optimizations of the nonlinear multi-modal function, many researchers have proposed several techniques such as the auto tuning niching genetic algorithm(ATNGA), and the climb method [1][2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Minimization of a Cogging Torque for an Interior Permanent Magnet Synchronous Machine using a Novel Hybrid Optimization Algorithm

Kim¹,

Woo²,

Lim³

et al. 2014

Journal of Electrical Engineering and Technology

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-Optimization of an electric machine is mainly a nonlinear multi-modal problem. For the optimization of the multi-modal problem, many function calls are required with much consumption of time. To address this problem, this paper proposes a novel hybrid algorithm in which function calls are less than conventional methods. Specifically, the proposed method uses the kriging metamodel and the fill-blank technique to find an approximated solution in a whole problem region. To increase the convergence speed in local peaks, a parallel gradient assisted simplex method is proposed and combined with the kriging meta-model. The correctness and usefulness of the proposed hybrid algorithm is verified through a mathematical test function and applied into the practical optimization as the cogging torque minimization for an interior permanent magnet synchronous machine.

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Hybrid Optimization Strategy using Response Surface Methodology and Genetic Algorithm for reducing Cogging Torque of SPM

Cited by 16 publications

References 3 publications

Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

Optimal design of interior permanent magnet synchronous motor considering the manufacturing tolerances using Taguchi robust design

Minimization of a Cogging Torque for an Interior Permanent Magnet Synchronous Machine using a Novel Hybrid Optimization Algorithm

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