• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1303-1307
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• 2018

A improving sensorless compensator for the IPMSM(Interior Permanent Magnet Synchronous Motor) drive system is proposed. Generally, the motor drive system is required the robust parameter variation and disturbance. The speed estimation methods of the conventional IRP(Instantaneous Reactive Power) compensator is improved by the speed estimation techniques of the current model observer with the proposed instantaneous reactive power compensator. Performance evaluations of the novel speed error compensator and sensorless control system are carried out by the experiments.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.3
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• pp.289-295
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• 2013

It is important to know exact values of Interior Permanent Magnet Synchronous Motors(IPMSM)' parameters such as stator resistance and inductance in order to have their high performance. This paper proposes a novel motor parameter(stator resistance, d&q axis inductance) estimation algorithm for IPMSM. The proposed estimation method utilizes back-EMF equations and model reference adaptive system(MRAS). The algorithm using back-EMF estimates d and q axis inductances in the constant torque region, and the stator resistance is estimated by using MRAS with the estimated inductance regardless of speed regions. The validity of the proposed algorithm is verified by simulations and experiments.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.761-762
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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 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.1
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• pp.18-25
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• 2013

In this paper, a nonlinear controller based on adaptive back-stepping method is proposed for high performance operation of Interior Permanent Magnet Synchronous Motor (IPMSM). First, in order to improve the performance of speed tracking, a nonlinear back-stepping controller is designed. In addition, since it is difficult to achieve the high quality control performance without considering parameter variation, a parameter estimator is included to adapt to the variation of load torque in real time. Finally, for the efficiency of power consumption of the motor, controller is designed to operate motor with the minimum current for the required maximum torque. The proposed controller is tested through experiment with a 1-hp Interior Permanent Magnet Synchronous Motor (IPMSM) for the angular velocity reference tracking performance and load torque volatility estimation, and to test the Maximum Torque per Ampere (MTPA) operation. The result verifies the efficacy of the proposed controller.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.110-116
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• 2017

This paper proposed a new real-time parameter tracking algorithm. Unlike the convenience algorithms, the proposed real-time parameter tracking algorithm can estimate parameters through three-phase voltage and electric current without coordination transformation, and does not need information on magnetic flux. Therefore, it can estimate parameters regardless of the change according to operation point and cross-saturation effect. In addition, as the quasi-real-time parameter tracking technique can estimate parameters through the four fundamental arithmetic operations instead of complicated algorithms such as numerical value analysis technique and observer design, it can be applied to low-performance DSP. In this paper, a new real-time parameter tracking algorithm is derived from three phase equation. The validity and usefulness of the proposed inductance estimation technique is verified by simulation and experimental results.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.4
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• pp.357-367
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• 1999

When traction system of 2-motor driven electric vehicle(EV) is consisted of two motors (IPMSM) . two inverters. and one traction controller, control performances of IPMSM for an electric vehicle is affected by parameter variation b because of large current magnitude and wide current phase angle. To solve this problem, new parameter estimator for L Ld and Lq is constructed by neu때 network technique. And new vector control algorithm with parameter estimator by n neural network is proposed for IPMSM.And also. an advanced traction control algorithm is proposed using fuzzy c controller in order to enhance the driveability oftwo-wheel drive EVs with fitted with a traction control system Performances of the proposed algorithm are examined by simulations and the experimental resul않 with respect to t the prototype IPMSM and EV.

• Proceedings of the KIPE Conference
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• 2011.07a
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• pp.567-568
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• 2011

영구자석 동기 전동기의 센서리스 구동에 있어서 위치와 속도를 정확히 추정하는 것이 중요하다. 정확한 위치와 속도의 추정을 위해서는 정확한 모터 파라미터가 필요한데, 특히나 magnetic saturation에 의한 q-축 인덕턴스의 영향이 가장 크기 때문에 이 논문에서는 매입형 영구자석 동기 전동기(IPMSM)의 센서리스 구동을 위한 q축 인덕턴스 추정에 대한 시뮬레이션 결과와 실험 결과를 나타내었다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.496-501
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• 2009

Interior Permanent Magnet Synchronous Motor (IPMSM) produces two kind of torque that Magnetic and Reluctance torque. The permanent magnet linkage flux ${\Psi}_a$ and d-axis and q-axis inductances have an important influence on the torque characteristic of IPMSM. Thus their accurate prediction is essential for predicting performance aspect such as the torque and flux-weakening capabilities. In this paper, the influence of barrier width on the ${\Psi}_a$ and $L_d$, $L_q$ is calculated by FEM analysis. Predictions are validated by comparison the average torques, using Maxwell Stress Tensor method.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2526-2528
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• 1999

Parameters of equivalent circuit of IPMSM are varied according to current magnitude and current phase angle. Especially, Parameter variation of IPMSM for an electric vehicle(EV) is critical. Because current magnitude is very large. and current phase angle range also is wide. So, variation characteristics of $L_d$ and $L_q$ of the IPMSM are analyzed and verified through experiments. And then new parameter estimator of $L_d$ and $L_q$ that is constructed by neural network technique is suggested Using numerical method, the advanced characteristics of current controller of vector control algorithm is verified.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.214-216
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• 2005

IPMSM is necessary to use the accurate values of the inductance for the precise torque control, because of using the reluctance torque of the IPM. This paper presents method to uses the hysteresis loop inclination of the flux and current measured by applying the positive and negative voltage pulse alternately on the each-axis. Moreover, presents algorithm for speed sensorless control based on parameter identification and instantaneous reactive power.