• 조명전기설비학회논문지
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• 제24권9호
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• pp.118-123
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• 2010

The selection of flux level in the maximum torque control of stator flux-oriented induction motor drives in the field weakening region is dependent on stator resistance and inductances. This paper presents parameter detuning effects of stator flux-oriented control drives in the field weakening region. The detuning effects of stator resistance and rotor leakage inductance are analyzed. The decrease of torque and the flux control lost by the detuning of inductance are shown in the simulation results.

• 전기학회논문지
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• 제59권2호
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• pp.318-327
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• 2010

This paper deals with analysis on dynamic characteristic and circuit parameter of linear switched reluctance motor by electromagnetic analytical method. Above all, using space harmonic method, which is electromagnetic method, the air-gap flux density is analyzed in the both align and unaign positions, and the inductance profile, force characteristic and resistance per phase are calculated by means of the process. The validity of the analyzed results are demonstrated by the finite element method(FEM) and manufacture of the prototype machine. Second, the dynamic simulation is analyzed by the use of circuit parameters derived from analytical method, and the operating system of the prototype machine is manufactured to demonstrated the validity of simulation analysis. As a result, it is considered that the characteristic equation suggested in this paper will contribute to the design, analysis and application of LSRM.

• Journal of Power Electronics
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• 제3권1호
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• pp.55-61
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• 2003

This paper presents parameter measurement for permanent magnet synchronous motors based on the P-Q circle diagram. Three electrical parameters of permanent magnet synchronous motors, i.e., the equivalent iron loss resistance, armature inductance, and electrical motive force (emf) coefficient are simultaneously measured. The advantages of this method are that it can be implemented under constant excitation and it dispenses with the generating test for the emf coefficient. The proposed method is applied to a 160w permanent magnet synchronous motor, and then the measurement results are analyzed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2374-2376
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• 2000

In this paper, we propose an indirect vector control method using Adaptive Neuro-Fuzzy Inference System (ANFIS) parameter estimator. It estimates the rotor time constant when the indirect vector control of induction motor is applied. We use the stator current error that is difference between the current command and estimated current calculated from terminal voltage and current. And two induced current estimate equations are used in training ANFIS.The estimator is trained by the hybrid learning algorithm. Simulation results shows good performance under load disturbance and motor parameter variations.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.852-854
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• 1995

This paper proposes a new identification method that utilizes fuzzy inference in parameter identification. The prosed system has an additional control loop where a real plant has replaced by a plant model. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. In this paper, the tuning method which determines parameters of PID controller automatically is described through applying this algorithm to DC servo motor. And we intend to investigate effectiveness of the method by experiments. This method is effective in auto-tuning because the response of the closed loop has verified. The simulated and the experimental results of the dc servo motor are shown to confirm the viability of this method.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.2125-2133
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• 2018

To achieve high performance speed regulation, a robust adaptive speed controller is proposed for the permanent magnet synchronous motor (PMSM) subject to parameter uncertainties and input saturations in this paper. A nonlinear adaptive control is introduced to compensate the PMSM speed tracking errors due to uncertainties, disturbances and control input saturation constraints. By combining the adaptive control and the nonlinear robust control based on the interconnection and damping assignment (IDA) strategy, a new robust adaptive control is designed for speed regulation of PMSM. Stability and robustness of the closed-loop control system involved with the constrained control inputs rather than unconstrained control inputs are validated. Simulations for PMSM control in the presence of uncertainties and saturations nonlinearities show that the proposed approach is effective to regulate speed, and the average tracking error using the proposed approach is at least 32% smaller than the compared methods.

• 한국자기학회지
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• 제25권3호
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• pp.92-100
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• 2015

전기자동차는 구동방식에 따라 인휠(in-wheel) 방식과 인라인(in-line) 방식으로 구분될 수 있다. 인휠 방식 전기자동차는 기존의 자동차에서 사용하였던 변속기, 축, 차동기어 등을 제거 할 수 있기 때문에 구조가 간단해지고 차체를 경량화하여 효율을 증대시킬 수 있는 장점이 있다. 본 논문에서는 파라미터 맵(parameter map)을 이용한 차량용 인휠 전동기의 설계 방법을 제시하고, 연속정격 5 kW급 전동기를 설계하여 제작 및 성능 검증을 한다. 우선 차량의 요구 성능을 만족하는 인휠 전동기의 용량을 결정하기 위해 차량의 총무게, 기어 효율, 바퀴의 등가반경, 등판각도 등을 고려한 차량동특성해석을 수행한다. 이것을 통해 전동기 용량을 결정하고, 전동기 형상 및 치수를 결정하기 위한 초기설계를 진행한다. 그리고 요구 성능을 만족하는 전동기 파라미터를 결정하기 위해 파라미터 맵을 이용한 파라미터 설계를 수행한다. 파라미터 맵을 통해 전동기 파라미터를 결정한 후 마지막으로 무부하역기전력의 왜형율(Total Harmonic Distortion, 이하 THD), 코깅토크(cogging torque), 토크리플(torque ripple) 등의 개선을 위해 최적설계를 수행한다. 최종 설계 모델에 대해 제작을 하였으며, 성능 검증 및 제시한 설계방법의 신뢰도 검증을 위해 부하시험을 진행한다.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권5호
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• pp.332-337
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• 2004

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying. parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• 제어로봇시스템학회논문지
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• 제13권5호
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• pp.429-433
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• 2007

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.207-209
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• 2006

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.