• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
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• pp.274-276
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• 2009

This paper presents a rotor shape optimization of interior type permanent magnet (IPM) motor for cogging torque minimization and maximization of reluctance torque. In order to minimize the cogging torque, the optimal notches are put on the rotor pole face and the arc type pole face is applied. The variations of cogging torque and d-q axis inductions are analyzed by finite element method (FEM).

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제52권3호
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• pp.93-100
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• 2003

Switched reluctance motor(SRM) has some advantages such as low cost, high torque density but SRM has essentially high torque ripple due to its salient structure. In order to apply SRM to industrial field, torque ripple has to be reduced. This paper introduces optimal design process of SRM using an optimization algorithm of Progressive Quadratic Response Surface Modeling(PQRSM) and two-dimensional(2D) Finite Element Method(FEM). The electrical and geometrical design parameters have been adopted as 2D design variables. From this work, it can be obtained both the optimal design minimized torque ripple and the optima1 design maximized the average torque, respectively. Finally, this Paper Presents Performance comparison of two optimal designs and consider influence of the selected design variables in torque characteristics.

• Journal of Electrical Engineering and Technology
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• 제13권6호
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• pp.2262-2267
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• 2018

In electric machine design, there is a large computation cost for finite element analyses (FEA) when analyzing nonlinear characteristics in the machine Therefore, for the optimal design of an electric machine, designers commonly use an optimization algorithm capable of excellent convergence performance. However, robustness consideration, as this factor can guarantee machine performances capabilities within design uncertainties such as the manufacturing tolerance or external perturbations, is essential during the machine design process. Moreover, additional FEA is required to search robust optimum. To address this issue, this paper proposes a computationally efficient robust optimization algorithm. To reduce the computational burden of the FEA, the proposed algorithm employs a useful technique which termed static analysis assisted technique (SAAT). The proposed method is verified via the effective robust optimal design of electric machine to reduce cogging torque at a reasonable computational cost.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1334-1339
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• 2003

An efficient method is developed for the shape optimization of 2-D structures. The sequential linear programming is used for minimization problems. Selected set of master nodes are employed as design variables and assigned to move towards the normal direction. After adapting the nodes on the design boundary, the B-spline curves and mesh smoothing schemes are used to maintain the finite element in good quality. Finally, a numerical implementation of optimum design of an automobile torque converter piston subjected to pressure and centrifugal loads is presented. The results shows additional weight up to 13% may be saved after the shape optimization.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제51권2호
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• pp.55-60
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• 2002

This paper presents an optimization procedure by using Response Surface Methodology(RSM) to determine design parameters for reducing cogging torque. RSM is achieved through using the experimental design method in combination with Finite Element Method and adapted to make analytical model for a complex problem considering a lot of interaction of these parameters. Sequential Quadratic Problem (SQP) method is used to solve the relsulting of constrained nonlinear optimization problem.

• 한국지능시스템학회논문지
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• 제18권5호
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• pp.642-648
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• 2008

여자유도 매니퓰레이터의 동적 제어는 관절에 가해지는 토크를 최소화하는 목적으로 많은 연구가 이루어져 왔다. 그러나 기존의 국소 토크 최적화의 동적 제어 방법은 드라이버로 구현하기 힘든 토크가 요구된다. 본 논문에서는 그러한 큰 토크 요구를 상당히 개선시킨 새로운 제어 알고리즘을 제안한다. 이 알고리즘은 기존의 국소 토크 최소화 알고리즘에 퍼지 로직과 유전자 알고리즘을 적용시킨 것이다. 제안된 알고리즘은 3자유도 평면 여자유도 로봇에 적용하였으며, 시뮬레이션 결과를 통하여 제안된 알고리즘의 타당성을 확인하였다.

• Journal of Magnetics
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• 제21권4호
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• pp.577-585
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• 2016

In this paper, model of the axial-flux permanent magnet synchronous generator (AFPMSG) having arc-shaped trapezoidal permanent magnets (PM) is presented. The proposed model reduces the cogging torque and torque ripple, at the expense of lowering the average output torque. Optimization of the proposed model is performed by considering the asymmetric overhang configuration of the PMs, as to make the output torque of the proposed model competitive with the conventional model. The time stepped 3D finite element analysis (FEA) is performed for the comparative analysis. It is demonstrated that the torque ripple of the optimized model is highly reduced as well as average output torque is increased.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
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• pp.29-31
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• 2009

Optimal efficiency control of synchronous reluctance motor(SynRM) is very important in the sense of energy saving and conservation of natural environment because the efficiency of the SynRM is generally lower than that of other types of AC motors. This paper is proposed an efficiency optimization control for the SynRM which minimizes the copper and iron losses. The design of the speed controller based on fuzzy-neural networks (FN)-PI controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization control is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses In variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the proposed controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• 조명전기설비학회논문지
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• 제26권12호
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• pp.9-20
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• 2012

This paper proposes the efficiency optimization control of interior permanent magnet synchronous motor(IPMSM) drive using series connected-fuzzy neural network PI(SC-FNPI) controller. The PI controller is generally used to control IPMSM drive in industrial field. However, the PI controller has problem which is falling control performance about parameter variation such as command speed, load torque and inertia due to fixed gain of PI controller. Therefore, to improve performance of PI controller, this paper proposes SC-FNPI controller adjusted input of PI controller by FNN controller according to operating conditions. Also, this paper proposes efficiency optimization control which is improving efficiency with minimize loss. The SC-FNPI controller proposed in this paper is compared control performance with conventional FNN and PI controller about command speed, load torque and inertia variation. And the efficiency optimization control is compared with $i_d=0$ control about loss and efficiency. The SC-FNPI controller proposed in this paper shows more excellent control performance for rising time, overshoot and steady-state error. Also efficiency optimization control is increased efficiency by reducing loss.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.859-865
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• 2014

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.