• Journal of Power Electronics
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• v.17 no.5
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• pp.1211-1222
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• 2017

In order to decrease the parameter sensitivity of deadbeat direct torque control (DB-DTC), an improved deadbeat direct torque control method for surface mounted permanent-magnet synchronous motor (SPMSM) drives is proposed. First, the track errors of the stator flux and torque that are caused by model parameter mismatch are analyzed. Then a sliding mode observer is designed, which is able to predict the d-q axis currents of the next control period for one-step delay compensation, and to simultaneously estimate the model parameter disturbance. The estimated disturbance of this observer is used to estimate the stator resistance offline. Then the estimated resistance is required to update the designed sliding-mode observer, which can be used to estimate the inductance and permanent-magnetic flux linkage online. In addition, the flux and torque estimation of the next control period, which is unaffected by the model parameter disturbance, is achieved by using predictive d-q axis currents and estimated parameters. Hence, a low parameter sensitivity DB-DTC method is developed. Simulation and experimental results show the validity of the proposed direct control method.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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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.

• Proceedings of the KIEE Conference
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• 2006.04a
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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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.3
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• pp.238-244
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• 2004

To monitor the torque of an induction motor using current, the accurate identification of the motor parameters is very important. In this study, the motor parameters such as rotor resistance, stator and rotor leakage inductance, mutual inductance are estimated for torque monitoring and indirect vector control. Estimated parameters are used to monitor the torque of vector controlled induction motor without any speed measuring sensor. Stator current is measured to estimate the magnetizing current which is used to calculate flux linkage, rotor velocity and motor torque. From the experiments, the proposed method shows a good estimation of the motor parameters and torque under the normal rotational speed.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.235-237
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• 1999

This paper has proposed a method to estimate effective length of a 30 KVA super-conducting generator using 3-dimensional FEM program. Flux linkage of the stator coil is calculated by the FEM program and the induced voltage is computed using the simple Faraday's law.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.6
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• pp.59-65
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• 2009

In this paper study on a toroidal switched reluctance motor(TSRM) is described. The structure of the TSRM is different from that of a conventional SRM The main windings of the TSRM are wound around york of the stator while those of the conventional SRM are wound around its stator poses. Therefore the TSRM has many advantages and drive system, winding connection, inductance, drive method, torque, current waveform of the TSRM are different from those of the conventional SRM In this paper, the TSRM is analysed by simulation and experiment.

• 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.

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.1
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• pp.54-60
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• 2012

In this paper, a new permanent-magnet (PM) linear motor is proposed, in which both the magnets and armature windings are placed in the short mover, while the long stator consists of iron core only. Hence, this new PM linear motor can be called a primary permanent-magnet linear motor. It exhibits the advantages of robustness, low cost, high efficiency, high power factor, and high thrust force density. It is especially suitable for long stator applications such as urban rail transit. In this paper, the topology and operation principle of this motor are discussed in detail. The steady-state characteristics including field distributions, flux-linkage, back-EMF, phase inductance and thrust force are investigated. In addition, the technique of skewing stator teeth is adopted to improve the electromagnetic performance. Results from finite element method (FEM) verified the theoretical analysis results.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1614-1622
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• 2014

A novel equivalent flux sliding-mode observer (SMO) is proposed for dual three-phase interior permanent magnet synchronous motor (DT-IPMSM) drive system in this paper. The DT-IPMSM has two sets of Y-connected stator three-phase windings spatially shifted by 30 electrical degrees. In this method, the sensorless drive system employs a flux SMO with soft phase-locked loop method for rotor speed and position estimation, not only are low-pass filter and phase compensation module eliminated, but also estimation accuracy is improved. Meanwhile, to get the regulator parameters of current control, the inner current loop is realized using a decoupling and diagonal internal model control algorithm. Experiment results of 2MW-level DT-IPMSM drives system show that the proposed method has good dynamic and static performances.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.205-207
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• 1994

This paper presents an analyzing method of the distortion factor of the output voltage in generator on the basis of the stator coil flux linkage calculation. In the simulation, 2 dimensional finite clement method is used considering the rotor movement. As an application of the proposed method, we calculated the harmonics of air gap flux and the output voltage in the 150KW class synchronous generator.