A Novel Memetic Algorithm Using Modified Particle Swarm Optimization and Mesh Adaptive Direct Search for PMSM Design

Lee, Jin Hwan; Kim, Jong-Wook; Song, Jun-Young; Kim, Yong-Jae

doi:10.1109/tmag.2015.2482975

Cited by 52 publications

(27 citation statements)

References 11 publications

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“…Optimal design is a method of finding the values of design variables to obtain an optimal solution within a range of constraints. The optimal design for PMSMs is created by combining design methods such as the analytical model, magnetic equivalent circuits (MEC) model, and finite element analysis (FEA) with optimal design algorithms [1][2][3][4][5][6][7][8]. First of all, there are studies on optimal design using the analytical model [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…K-means clustering algorithm was utilized to obtain the best solution out of the eight clusters. Finally, some research on optimization combined with FEA have been published [5][6][7]. The work in [5] performed multi-objective shape optimization of a PMSM based on FEA and particle swarm optimization algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…It performed shape optimization of permanent magnets and rotor core using FEA with the fuzzy inference system strategy. Using a novel memetic algorithm, an optimal design based on FEA to minimize torque ripple in a PMSM was created [7]. In [8], multi-physics and multi-objective optimization of a PMSM based on FEA and analytical magnetic model were studied.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Design of PMSM Based on Automated Finite Element Analysis and Metamodeling

You

2019

Energies

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To obtain accurate optimal design results in electric machines, the finite element analysis (FEA) technique should be used; however, it is time-consuming. In addition, when the design of experiments (DOE) is conducted in the optimal design process, mechanical design, analysis, and post process must be performed for each design point, which requires a significant amount of design cost and time. This study proposes an automated DOE procedure through linkage between an FEA program and optimal design program to perform DOE easily and accurately. Parametric modeling was developed for the FEA model for automation, the files required for automation were generated using the macro function, and the interface between the FEA and optimal design program was established. Shape optimization was performed on permanent magnet synchronous motors (PMSMs) for small electric vehicles to maximize torque while maintaining efficiency, torque ripple, and total harmonic distortion of the back EMF using the built-in automation program. Fifty FEAs were performed for the experimental points selected by optimal Latin hypercube design and their results were analyzed by screening. Eleven metamodels were created for each output variable using the DOE results and root mean squared error tests were conducted to evaluate the predictive performance of the metamodels. The optimization design based on metamodels was conducted using the hybrid metaheuristic algorithm to determine the global optimum. The optimum design results showed that the average torque was improved by 2.5% in comparison to the initial model, while satisfying all constraints. Finally, the optimal design results were verified by FEA. Consequently, it was found that the proposed optimal design method can be useful for improving the performance of PMSM as well as reducing design cost and time.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal Design of PMSM Based on Automated Finite Element Analysis and Metamodeling

You

2019

Energies

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“…The most popular method of them is particle swarm optimization (PSO) [29][30][31][32], which has been widely used in many optimization problems. It has the ability to solve difficult optimization problems and converge quickly to a solution [33][34][35][36]. Although the PSO was developed primarily to address unconstrained optimization problems; nevertheless, it performs well when applied to constrained optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation of Electromechanical Oscillation Based on a Constrained EKF with C&I-PSO

et al. 2018

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By combining together the extended Kalman filter with a newly developed C&I particle swarm optimization algorithm (C&I-PSO), a novel estimation method is proposed for parameter estimation of electromechanical oscillation, in which critical physical constraints on the parameters are taken into account. Based on the extended Kalman filtering algorithm, the constrained parameter estimation problem is formulated via the projection method. Then, by utilizing the penalty function method, the obtained constrained optimization problem could be converted into an equivalent unconstrained optimization problem; finally, the C&I-PSO algorithm is developed to address the unconstrained optimization problem. Therefore, the parameters of electromechanical oscillation with physical constraints can be successfully estimated and better performed. Finally, the effectiveness of the obtained results has been illustrated by several test systems.

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“…Design of efficient and customized motors which are destined to present specific behavior and reach predefined characteristics, depends on the selection of the best possible combination of motor parameters. Since there are too many parameters which influence the motor's static and dynamic performances, choice of an optimal pattern of parameters could be really complicated and time consuming [1], [2], [3]. The first step of an optimized design of an electrical motor is a proper description of its electric and magnetic characteristics.…”

Section: Introductionmentioning

confidence: 99%

Design Optimization of Permanent Magnet

Ebrahimi¹

2018

Preprint

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A multilevel ant algorithm is developed to optimize thedesign process of a surface mounted permanent magnetsynchronous motor. The motor properties are calculated using anexact magnetic equivalent circuit based analytical model. Thismodel takes into account the iron saturation, the slot stray fluxesand the spatial harmonics of rotor and stator fluxes. Theeffectiveness of the proposed analytical model is verified incomparison with measurement of a handmade prototype. Basedon this analytical model the air gap flux density, torque andinduced voltage of the prototype motor are predicted. For aneffective selection of motor parameters, a multipurposeoptimization algorithm is developed, which is based on thedistributed multilevel ant-stigmergy algorithm. The analyticalmodel together with the optimization algorithm represents a veryeffective tool for design of permanent magnet synchronous motorwithout any need for time consuming finite element programs.

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A Novel Memetic Algorithm Using Modified Particle Swarm Optimization and Mesh Adaptive Direct Search for PMSM Design

Cited by 52 publications

References 11 publications

Optimal Design of PMSM Based on Automated Finite Element Analysis and Metamodeling

Optimal Design of PMSM Based on Automated Finite Element Analysis and Metamodeling

Parameter Estimation of Electromechanical Oscillation Based on a Constrained EKF with C&I-PSO

Design Optimization of Permanent Magnet

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