• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.107-109
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• 2007

Pancake windings have merits that are easier to make high field magnets and replace windings when an accident happens and windings are aged. The current of the whole magnet consisted of windings connected in series was limited by the minimum current of the top and bottom pancake windings where maximum perpendicular magnetic field was applied. This paper propose a optimal design of a HTS magnet excited by a single source, where evolution strategy was adopted for optimal design algorithm. A magnet consisted of 8 BSCCO pancakes was chosen to prove the effectiveness of this optimal design method. Magnetic field at the center of a magnet was chosen as the object function and it was used maximized. Results of the optimal design shows that the increment of the number of turns of the pancake winding make the magnetic field of the center of the magnet increase but the current of the winding decrease for the larger perpendicular magnetic field.

• Journal of Power Electronics
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• v.16 no.3
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• pp.982-993
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• 2016

A method for the fault-tolerant vector control of star-connected 3-phase Induction Motor (IM) drive systems based on Field-Oriented Control (FOC) is proposed in this paper. This method enables the control of a 3-phase IM in the presence of an open-phase failure in one of its phases without the need for control structure changes to the conventional FOC algorithm. The proposed drive system significantly reduces the speed and torque pulsations caused by an open-phase fault in the stator windings. The performance of the proposed method was verified using MATLAB (M-File) simulation as well experimental tests on a 1.5kW 3-phase IM drive system. This paper experimentally compares the operation of the proposed fault-tolerant vector controller and a conventional vector controller during open-phase fault.

• Journal of Magnetics
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• v.22 no.1
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• pp.104-108
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• 2017

Induction motors have wide applicability in many fields, both in industrial sectors and households, for their advantages of a high efficiency and robust structure. The introduction of power-source-containing harmonics into the induction motor winding lowers its efficiency and increases its temperature, greatly affecting its operation characteristics. In this study, we performed an electromagnetic field analysis using the time-difference finite-element method with the purpose of analyzing the steady-state current characteristics of an induction motor. Additionally, we calculated the steady-state current with a method combining an electromagnetic field equation and a circuit equation. In the electromagnetic field analysis, the nonlinearity was taken into account using the Newton-Raphson method, and a backward time-difference method was employed for the time derivative term. Then, we compared the steady-state current of the induction motor obtained by calculation with the experimentally measured values, thus validating the proposed algorithm. Furthermore, we analyzed the impacts of the shape and material of the rotor conductor bar of the induction motor on the steady-state current of the main winding.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.1
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• pp.52-60
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• 2018

The winding of the motor stator coil is broken due to external stress and various factors. If the proper current is not injected when interturn fault(ITF) occurs, the fault can easily be expanded and the motor can be finally destroyed, resulting in many problems with time costs and safety. In this paper, the power loss limit concept, which is the inherent durability of each motor, is applied to secure safety by controlling the total power loss of the motor within the limits. So, we propose an algorithm that can control maximum torque per minimum power loss based on constant torque curve and power loss limit. To verify the proposed method, the simulation and experimental results with an Interior permanent magnet synchronous motor(IPMSM) having an ITF are shown.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.363-365
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• 2006

This paper proposes an estimation method for a circulating current of a Y-${\Delta}$ Transformer. The delta winding current can be decomposed into the two components i.e. a non-circulating component and a circulating component. The former can be estimated using the line currents. However, the latter can not be estimated directly using the line currents. A first order differential equation for the circulating current is derived by applying the Kirchhoff's voltage law on the loop of the delta side. The circulating current can be estimated by the solving the differential equation. The performance of the proposed algorithm is investigated under various conditions including magnetic inrush and over-excitation. The algorithm can estimate the circulating current very accurately even under magnetic inrush and over-excitation.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.95-97
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• 2006

This paper investigates the field weakening operation of a five-phase IPMSM(inner permanent magnet synchronous motor). The five-phase motor can supply sinusoidal voltage and third harmonic voltage because of more freedom of control. This paper present field weakening algorithm and experimental results for five-phase IPMSM which has trapzoidal back-EMF and concentrate winding to prove the validity of the proposed algorithm.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.365-371
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• 2006

This paper presents an algorithm based on a combination of Discrete Wavelet Transforms and neural networks for detection and classification of internal faults in a two-winding three-phase transformer. Fault conditions of the transformer are simulated using ATP/EMTP in order to obtain current signals. The training process for the neural network and fault diagnosis decision are implemented using toolboxes on MATLAB/Simulink. Various cases and fault types based on Thailand electricity transmission and distribution systems are studied to verify the validity of the algorithm. It is found that the proposed method gives a satisfactory accuracy, and will be particularly useful in a development of a modern differential relay for a transformer protection scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.335-341
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• 2009

Analysis of the partial discharge signal, a technique to diagnose the stator winding insulation is a key function for the diagnosis of high voltage rotating machines and requires high precision. To satisfy this requirement, various denoising techniques such as filtering and differential methods were proposed. However, these techniques can not eliminate a adjacent induction noise that decreases reliability of the diagnosis. A simple novel denoising algorithm, therefore, is proposed for removing the adjacent induction noise in this paper. The algorithm shows good performance in the real partial discharge signals measured by 13kV class capacitive couplers installed at hydro-generator in Dae-cheong Dam.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1039-1041
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• 2000

To obtain a high performance in a vector controlled induction machine, it is essential to know the instantaneous position of the rotor flux which depends on the rotor time constant. But the rotor time constant mainly varies due to the temperature rise in the motor winding, so real time compensating algorithm is necessary. This paper proposes that it uses short duration pulses added to the constant flux command current and then resultant torque command current produced by speed controller is utilized for the rotor resistance estimation. This method has advantages with a low computational requirement and does not require voltage sensors. The proposed method is proved by simulations.

• Journal of Power Electronics
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• v.6 no.3
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• pp.245-252
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• 2006

This paper presents a method based on neural networks to detect the broken rotor bars and end rings of squirrel cage induction motors. At first, detection methods are studied, and then traditional methods of fault detection and dynamic models of induction motors by using winding function model are introduced. In this method, all of the stator slots and rotor bars are considered, thus the performance of the motor in healthy situations or breakage in each part can be checked. The frequency spectrum of current signals is derived by using Fourier transformation and is analyzed in different conditions. In continuation, an analytical discussion and a simple algorithm are presented to detect the fault. This algorithm is based on neural networks. The neural network has been trained by using information of a 1.1 KW induction motor. This system has been tested with a different amount of load torque, and it is capable of working on-line and of recognizing all normal and ill conditions.