• Progress in Superconductivity and Cryogenics
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• v.26 no.1
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• pp.1-4
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• 2024

This study explores the use of a bulk type high-temperature superconductors (HTS) as trapped field magnets in synchronous motors. A HTS bulk is examined for its ability to generate powerful magnetic fields over a permanent magnet and to eliminate the need for a direct power supply connection compared to a tape form of HTS. A 150 kW interior-mounted bulk-type superconducting synchronous motor is designed and analyzed. The A-H formulation is used to numerical analysis. The results show superior electrical performance and weight reduction when comparing the designed model with the conventional permanent magnet synchronous motor of the same topology. This study presents HTS bulk synchronous motor's overall design process and highlights its potential in achieving relatively high power density than conventional permanent magnet synchronous motor.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.3
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• pp.165-173
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• 2013

Core loss has a major effect on heat generation in synchronous motors with surface-mounted permanent magnets (SPMs). It is essential to perform heat transfer analysis considering core loss in SPM because core loss is seriously affected by torque and speed of motors. In the present study, mechanical loss, core loss and coil loss are evaluated by measuring input and output energies under various driving conditions. For a better understanding heat transfer paths in synchronous motors, we developed a lumped thermal system analysis model. Subsequently, heat transfer analysis has been performed based on acquired energy loss, temperature data and thermal resistance with three types of SPM. It is shown that the torque constants decrease by Max. 10% as speed increase. At the rated torque, the core loss is Max. 10.9 times greater than the coil loss and the hysteresis loss of magnets is dominant in total loss.

• Journal of Power Electronics
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• v.9 no.6
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• pp.940-948
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• 2009

The main objective of this a paper is to improve the efficiency of permanent magnet synchronous motors (PMSMs) by using an improved direct torque control (DTC) strategy. The basic idea behind the proposed strategy is to predict the impact of a small change in the stator flux amplitude at each sampling period to decrease electrical loss before the change is applied. Accordingly, at every sampling time, a voltage vector is predicted and applied to the machine to fulfill the flux change. The motor drive simulations confirm a significant improvement in efficiency as well as a very fast and smooth response under the proposed strategy.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.416-424
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• 2016

In this study, automatic detection of stator winding inter-turn short circuit fault (SWISCFs) in surface-mounted permanent magnet synchronous motors (SPMSMs) and automatic classification of fault severity via a pattern recognition system (PRS) are presented. In the case of a stator short circuit fault, performance losses become an important issue for SPMSMs. To detect stator winding short circuit faults automatically and to estimate the severity of the fault, an artificial neural network (ANN)-based PRS was used. It was found that the amplitude of the third harmonic of the current was the most distinctive characteristic for detecting the short circuit fault ratio of the SPMSM. To validate the proposed method, both simulation results and experimental results are presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.635-641
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• 2016

In many industrial applications that use the electric motors robust controllers are needed. The method using a neural network in order to design a robust controller when a disturbance occurs is studied. Backpropagation algorithm, which is used in a conventional neural network controller is used in many areas, but when the number of neurons in the input layer, hidden layer and output layer of the neural network increases the processing speed of the learning process is slow. In this paper an adaptive PI(Proportional and Integral) controller based on CTRNN(Continuous Time Recurrent Neural Network) for permanent magnet synchronous motors is presented. By varying the load and the speed the validity of the proposed method is verified through simulation and experiments.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.12
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• pp.789-796
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• 2000

This paper deals with magnetic field and characteristic analysis for ring type slotless synchronous motors by using analytical method. Since magnetic air-gap in the slotless motors is much larger than mechanical air-gap, it is necessary to analyze the magnetic flux distribution at the whole magnetic airgap region. therefore, this paper analyzes the duplicated magnetic field derived by both Permanent Magnet(PM) and armature current and estimates the back electromotive force and torque characteristic by subdividing the conductor region. The analysis results are verified by comparing with Finite Element Analysis(FEA) results.

• Journal of Power Electronics
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• v.3 no.1
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.10
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• pp.1481-1487
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• 2017

This paper proposes a sensorless speed control algorithm for parallel-connected dual Surface-mounted Permanent Magnet Synchronous Motors fed by a single inverter. For stable parallel operation of synchronous motors with a single inverter, each motor has to be constantly kept in the synchronization state regardless of load torque. If the master motor with the larger load is controlled, the synchronous state will be maintained. Therefore, detection of the master motor is essential. Conventionally, the master motor is determined by comparing the rotor position error from the relation between the back-EMF for torque angle and the flux position. consequently, the position sensor is deemed essential for finding the rotor position. In this paper, we proposed a method that decides the magnitude of the load from the power angle of two motors due to the load variation and selects the motor to control through the sign function for the sensorless speed control without the position sensor. The results of simulation and experiment conducted verify the efficacy of the proposed method.

• Journal of Power Electronics
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• v.6 no.3
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• pp.235-244
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• 2006

Recently, speed sensorless vector control for synchronous reluctance motors (SYRMs) has deserved attention because of its advantages. Although rotor angle calculation using flux estimation is a straightforward approach, the DC offset can cause an increasing pure integrator error in this estimator. In addition, this method is affected by parameter fluctuation. In this paper, to control the motor at the low speed region, a modified programmable cascaded low pass filter (MPCPLF) with sensorless online parameter identification based on a block pulse function is proposed. The use of the MPCLPF is suggested because in programmable, cascade low pass filters (PCLPF), which previously have been applied to induction motors, the drift increases vastly wl)en motor speed decreases. Parameter identification is also used because it does not depend on estimation accuracy and can solve parameter fluctuation effects. Thus, sensorless speed control in the low speed region is possible. The experimental system includes a PC-based control with real time Linux and an ALTERA Complex Programmable Logic Device (CPLD), to acquire data from sensors and to send commands to the system. The experimental results show the proposed method performs well, speed and angle estimation are correct. Also, parameter identification and sensorless vector control are achieved at low speed, as well as, as at high speed.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2315-2325
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• 2015

Induction motors are widely used in industrial processes since they offer a very high degree of reliability. But like any other machine, they are vulnerable to faults, which if left unmonitored, might lead to an unexpected interruption at the industrial plant. Therefore, the condition monitoring of the induction motors have been a challenging topic for many electrical machine researchers. Indeed, the effectiveness of the fault diagnosis and prognosis techniques depends very much on the quality of the fault features selection. However, in induction-motor drives, rotor defects are the most complex in terms of detection since they interact with the supply frequency within a restricted band around this frequency, especially in the no-loaded case. To overcome this drawback, this paper deals with an efficient and new method to diagnose the induction-motor rotor fault based on the digital implementation of the monitoring algorithm based on the association of the Time Synchronous Averaging technique and Discrete Wavelet Transform. Experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the combined “Time Synchronous Averaging – Discrete Wavelet Transform” approach.