Heuristic Optimization Based on Penalty Approach for Surface Permanent Magnet Synchronous Machines

Mutluer, Mümtaz; Şahman, Mehmet Akif; Çunkaş, Mehmet

doi:10.1007/s13369-020-04689-y

Cited by 20 publications

(13 citation statements)

References 36 publications

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“…This algorithm is different from the velocity and position update equations in the traditional PSO. In the proposed AR-DPSO, the equations (20) and (21) are used to determine the velocity and position of the particle at the next moment in the iteration process, as bellow:…”

Section: Aar-dpsomentioning

confidence: 99%

“…In [19], a new algorithm was proposed to reduce iron loss by optimizing the traditional SC through combining fuzzy logic controller (FLC) and golden section method (GSM-SC). However, the traditional SC strategy is based on the static decoupling characteristic of the vector control algorithm, and as the optimization algorithm is implemented, the change in magnetic flux will destroy this characteristic and cause the fluctuation in the output torque [20]. In [21], in order to improve the operation efficiency of PMSM, traditional GSM-SC is used to obtain the optimal daxis current by controlling the d-axis current based on the analysis of the PMSM loss model.…”

Section: Introductionmentioning

confidence: 99%

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Operation Efficiency Optimization for Permanent Magnet Synchronous Motor Based on Improved Particle Swarm Optimization

Chen

Shu

et al. 2021

IEEE Access

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Section: Aar-dpsomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Operation Efficiency Optimization for Permanent Magnet Synchronous Motor Based on Improved Particle Swarm Optimization

Chen

Shu

et al. 2021

IEEE Access

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“…Also, the calculations for GA procedure for parameters: population size equal N=32, probability of mutation p m =0,007 were executed. The optimization procedure consists of three genetic operators: reproduction, crossover and mutation [27]. Additionally, the simple elitism procedure has been applied to save the best individual during genetic operations, especially mutation procedure.…”

Section: Calculations For the Ga Algorithmmentioning

confidence: 99%

“…This group of algorithms consists of: the Ant Colony Optimization (ACO) algorithm [26], the Cuckoo Search (CS) algorithm [5,37], the Bat Algorithm (BA) [4] and the Gray Wolf Optimizer (GWO) algorithm [14]. Optimization calculations are often performed on simplified models (analytical or lumped parameters) of the PM motors [14,26,27]. There are not many articles on the subject of optimization algorithms using 2D FEA models and gray wolf optimization.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2021

EiN

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This paper presents the algorithm and computer software for constrained optimization based on the gray wolf algorithm. The gray wolf algorithm was combined with the external penalty function approach. The optimization procedure was developed using Borland Delphi 7.0. The developed procedure was then applied to design of a line-start PM synchronous motor. The motor was described by three design variables which determine the rotor structure. The multiplicative compromise function consisted of three maintenance parameters of designed motor and one non-linear constraint function was proposed. Next, the result obtained for the developed procedure (together with the gray wolf algorithm) was compared with results obtained using: (a) the particle swarm optimization algorithm, (b) the bat algorithm and (c) the genetic algorithm. The developed optimization algorithm is characterized by good convergence, robustness and reliability. Selected results of the computer simulation are presented and discussed.

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“…Permanent magnet synchronous motors (PMSM) are preferred in many industrial applications for reasons such as providing high torque at low speeds, high power density and high efficiency [Mutluer et al, 2020]. Contrary to the works in which gear system is used, the fact that it offers gearless operation makes PMSM more preferred.…”

Section: Introductionmentioning

confidence: 99%

Dış Rotorlu Yüzeye Monte PMSM için Vuruntu Momentinin İncelenmesi

Mutluer¹

2021

European Journal of Science and Technology

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One of the most important structural problems for permanent magnet synchronous motors is the cogging torque. One of the most effective ways to reduce the cogging torque is that magnets or slots are skewed. However, this will negatively affect the motor cost and production time. On the other hand, the cogging torque depends on the change in the reluctance of the motor in the air gap during operation. Therefore, the most important design approach to reduce the cogging torque is to examine the parameters that affect the air gap reluctance. In this study, the change of air gap reluctance of surface mounted permanent magnet synchronous motor with outer rotor during operation is investigated. For this purpose, the five most important parameters affecting the air gap reluctance change are selected. In this way, the best motor model with low cogging torque is tried to be obtained.

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Heuristic Optimization Based on Penalty Approach for Surface Permanent Magnet Synchronous Machines

Cited by 20 publications

References 36 publications

Operation Efficiency Optimization for Permanent Magnet Synchronous Motor Based on Improved Particle Swarm Optimization

Operation Efficiency Optimization for Permanent Magnet Synchronous Motor Based on Improved Particle Swarm Optimization

Untitled

Dış Rotorlu Yüzeye Monte PMSM için Vuruntu Momentinin İncelenmesi

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