• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.159-161
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• 1997

This paper presents a method of reducing cogging torque and improving average torque by changing the dead zone angle of trapezoidal magnetization distribution of rotor magnet in ring type. Because brushless d.c. motor has 3D shape of overhang, 3D analysis should be used for computation of its magnet field. In this paper, Three Dimensional Equivalent Magnetic Circuit Network method (3DEMCN) which can calculate an accurate 3D magnetic field has been introduced. The method has an advantage that nonlinear magnetic phenomena can be considered and the cogging torque analyses requesting the rotation of the rotor can be performed by the variation of magnetization distribution without remesh.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.11
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• pp.597-603
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• 1999

Due to its simple construction, operation steadiness and low cost, claw pole step motor is widely used for OA machine and automobile. This paper deals with analysis fo claw pole motor, especially eyeing to dynamic characteristics. To analyze dynamic characteristics of claw pole step motor, torque development in each angular step of rotor are surveyed and torque equation is drived using permeance method. To adopt the airgap MMF, the magnetic equivalent circuit of the motor is introduced. On the base of the magnetic equivalent circuit, the air gap flux equation is derived. To get a optimum design of the motor, the torque characteristic is studied in variation of coil data and remanence value of permanent magnetic material.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.293-300
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• 2011

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 and adaptive fuzzy learning contrroller(AFLC) for speed control in IPMSM Drives. AFLC is chaged fuzzy rule base by rule base modifier for robust control of IPMSM. 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 and AFLC is confirmed by comparing to conventional algorithm.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.1
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• pp.6-12
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• 2007

In this paper, an robust adaptive backstepping controller is proposed for the speed control of separately excited DC motor in pure electric vehicles. A general electric drive train of PEV is conceptually rearrange to major subsystems as electric propulsion, energy source, and auxiliary subsystem and the load torque is modeled by considering the aerodynamic, rolling resistance and grading resistance. Armature and field resistance, damping coefficient and load torque are considered as uncertainties and noise generated at applying load torque to motor is also considered. It shows that the backstepping algorithm can be used to solve the problems of nonlinear system very well and robust controller can be designed without the variation of adaptive law. Simulation results are provided to demonstrate the effectiveness of the proposed controller.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.600-608
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• 2014

This paper presents estimation of d-axis and q-axis inductance of an interior permanent magnet synchronous motor (IPMSM) by using an extended Kalman filter (EKF). The EKF is widely used for control applications including the motor sensorless control and parameter estimation. The motor parameters can be changed by temperature and air-gap flux. In particular, the variation of the inductance affects torque characteristics like the maximum torque per ampere (MTPA) control. Therefore, by estimating the parameters, it is possible to improve the torque characteristics of the motor. The performance of the proposed estimator is verified by simulations and experimental results based on an 11kW PMSM drive system.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.880-881
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• 2007

By reason of variation magnetic field, cogging torque is generated. Cogging torque of IPM is bigger than other type permanent magnet motor. So, this paper presents a Optimizeing notch to reduce cogging torque of interior type permanent magnet(: IPM) motor. Through Fourier formulation of magnetic field on rotor, we found position of notch and manufactured armature that is designed by optimizing analysis. The validity of the proposed design is confirmed with experiments.

• Journal of Magnetics
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• v.20 no.1
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• pp.91-96
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• 2015

As many researchers are relentlessly trying to improve the power generation schemes from the power grid, to meet the constantly increasing electricity demand. In this paper, the results of a finite element analysis are carried out to study on a design optimization of an asymmetric air-gap structure in 3-phase Permanent Magnet Brushless DC Motors. To achieve a high efficiency for a 3-phase PM BLDC motor, the asymmetric air-gap structure is proposed considering the rotation direction of a motor. Generally, a single-phase BLDC motor is applied asymmetric air-gap structure for starting. This is because the asymmetric air-gap structure causes reluctance variation so the motor can utilize reluctance torque toward a rotation direction. In this paper, the asymmetric air-gap is applied to 3-phase BLDC SPM motor so it utilizes reluctance torque with alignment torque. A proposed model is designed by 2-D FE analysis and the results are verified by experimental test.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.79-87
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• 2008

This paper proposes the design and implementation of a direct torque controlled induction motor drive system. The method is based on control of decoupling between amplitude and angle of reference stator flux for determining reference stator voltage vector in generating PWM output voltage for induction motors. The objective is to reduce electromagnetic torque ripple and stator flux droop which result in a decrease in current distortion in steady state condition. In addition, the proposed technique provides simplicity of a control system. The direct torque control is based on the relationship between instantaneous slip angular frequency and rotor angular frequency in adjustment of the reference stator flux angle. The amplitude of the reference stator flux is always kept constant at rated value. Experimental results are illustrated in this paper confirming the capability of the proposed system in regards to such issues as torque and stator flux response, stator phase current distortion both in dynamic and steady state with load variation, and low speed operation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.6
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• pp.414-419
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• 2015

Recently, commercial ships and other specialized vessels with electric propulsion system employ variable speed induction motor as its prime mover. The wide application of electrical motors also includes being the main drive system in most industrial machineries. However, during its start-up, shutdown, and brake switch operation, excessive torque variation are generated. As such, flexible coupling are installed in order to reduce the transmitted torque fluctuation to the driven side. In this paper, the pulse torque generated by an variable speed induction motor was analyzed theoretically and through measurement of torsional vibration. Induction motor with inverter on marine propulsion system and industrial compressor were used as experimental subjects. The study confirmed that pulse torque are generated regardless of motor speed and interpreted as a vibration source of the whole system. Results presented herein can be adopted as the basis in future amendment of inspection classifying body regulations.

• Journal of Power Electronics
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• v.8 no.4
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• pp.354-362
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• 2008

This paper presents neural load torque compensation method which is composed of a deadbeat load torque observer and gains compensation by a parameter estimator. As a result, the response of the PMSM (permanent magnet synchronous motor) obtains better precision position control. To reduce the noise effect, the post-filter is implemented by a MA (moving average) process. The parameter compensator with an RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural load torque observer to resolve problems. The neural network is trained in online phases and it is composed by a feed forward recall and error back-propagation training. During normal operation, the input-output response is sampled and the weighting value is trained multi-times by the error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against load torque and parameter variation. Stability and usefulness are verified by computer simulation and experiment.