Topology Optimization of Rotor Core Combined With Identification of Current Phase Angle in IPM Motor Using Multistep Genetic Algorithm

Okamoto, Yoshifumi; Tominaga, Yusuke; Wakao, Shinji; Sato, Shuji

doi:10.1109/tmag.2013.2285580

Cited by 41 publications

(13 citation statements)

References 8 publications

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“…This leads to long computational time which is necessary for search in high dimensional space. In addition, the fitness of individuals is computed in parallel [1]. Moreover, the heuristic local search (LS) is employed, because original GA hardly finds even heuristic local optima when chromosome size is long.…”

Section: A Ngnet-based Topology Optimization Methodsmentioning

confidence: 99%

“…For example, the rotor shape of interior permanent magnet (IPM) motor has been optimized with little dependence on experience and knowledge of engineers [1]- [3]. One of the well-known topology optimization methods is the on/off method with evolutionary algorithms (EA) [1], [2], [5], in which the optimization model is subdivided into small cells to which binary states, on (material) and off (air), are assigned. The model shape is optimized for the binary states using EA.…”

Section: Introductionmentioning

confidence: 99%

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Multimaterial Topology Optimization of Electric Machines Based on Normalized Gaussian Network

2015

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This paper presents a topology optimization method for multimaterial models based on the normalized Gaussian network (NGnet). In this method, one can determine optimal shapes of machines which are composed of various materials such as iron, magnet and nonmagnetic material. The present method is applied to the optimization of interior permanent magnet motor to determine the distributions of magnetic core and flux barrier as well as magnets. The optimization results show that average torque can be improved using as small amount of magnet as possible. In addition, characteristic of the present method is discussed in detail.Index Terms-interior permanent magnet motor, topology optimization.

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Section: A Ngnet-based Topology Optimization Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multimaterial Topology Optimization of Electric Machines Based on Normalized Gaussian Network

2015

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“…without introducing design parameters unlike the conventional parameter optimizations [1]- [3]. It has been shown that simple optimal shapes which are suitable for manufacturing can be obtained by the topology optimization when the material shape is represented through the liner combination of the basis functions [4].…”

Section: Introductionmentioning

confidence: 99%

Topology Optimization Using Basis Functions for Improvement of Rotating Machine Performances

Sasaki

Igarashi

2018

IEEE Trans. Magn.

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This paper presents a new topology optimization method based on basis functions for design of rotating machines. In this method, the core shape of a given rotating machine is represented by the linear combination of the basis functions. The shape is then freely deformed by changing the weighting coefficients to the basis functions to find the optimal shape. The proposed method is compared with the conventional shape optimization based on polygon morphing. The former is shown to outperform the latter in both IPM and synchronous motor models.

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“…However, the number of arrangement patterns of the permanent magnets is very enormous, and it is difficult to experimentally obtain a more effective arrangement. Therefore, we focused on genetic algorithm (GA) which is one of optimization algorithms effective for nonlinear objective function [6], which is used to obtain optimum shape of electrical motor in several studies [7,8]. Furthermore, we confirmed that the GA we used to obtain the optimal placement of permanent magnets, considering the interactions of the magnets with each other, improved the levitation stability of the system [9,10].…”

Section: Introductionmentioning

confidence: 99%

Effect of Optimal Placement of Permanent Magnets on the Electromagnetic Force in the Horizontal Direction

et al. 2018

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The surface quality of steel plates is deteriorated as they contact rollers while being conveyed during manufacturing processes. To solve this problem, we previously proposed a hybrid electromagnetic levitation system comprising electromagnets, permanent magnets, and a horizontal positioning control system for steel plates. Moreover, to increase stability, we proposed integrating these levitation systems. In this study, we aim to determine the optimal placement of permanent magnets in the levitation system to suppress the deflection of a levitated steel plate for cases where the magnetic field in the horizontal direction changes. Using a genetic algorithm, the optimal gap, number, and placement of permanent magnets in the system are obtained.

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Topology Optimization of Rotor Core Combined With Identification of Current Phase Angle in IPM Motor Using Multistep Genetic Algorithm

Cited by 41 publications

References 8 publications

Multimaterial Topology Optimization of Electric Machines Based on Normalized Gaussian Network

Multimaterial Topology Optimization of Electric Machines Based on Normalized Gaussian Network

Topology Optimization Using Basis Functions for Improvement of Rotating Machine Performances

Effect of Optimal Placement of Permanent Magnets on the Electromagnetic Force in the Horizontal Direction

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