• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.1175-1178
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• 2004

On-line partial discharge(PD) monitoring system has been developed to monitor in operating large motor stator insulations. This system makes use of remote diagnosis techniques for the evaluation of PD activity in the control center of thermal power plant. This system can be remotely accessed via a modem to build database, analyze status and interpret the pattern of PD activity. A personnel computer is generally connected to ten motors to continuous measurement of the PD activity. The test data can be easily interpreted by a maintenance staff. For assessing the condition of stator winding in motors, this system ensures a reliable measurement and accurate estimation. Capacitive couplers used for on-line PD measurement have been 80pF. The maximum PD magnitude(Qmax), PD pattern and normalized quantity number(NQN) were performed by this system.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.6-8
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• 1996

Induction Motors are preferred because of their ability to achieve higher power density, efficiency and reliability than permanent DC Motors for Electric Vehicle Drives. This paper describes induction motor design procedure to achieve high power density for EV using nonlinear optimization technique. Objective functions are considered to improve power density and a set of eight design variables is identified. As a numerical example, an induction motor of 15kW, 3 phase and 4 pole is designed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1882-1888
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• 2010

It is widely known that ESA(Electric Signature Analysis) method is very useful one for fault diagnosis of an induction motor. Online fault diagnosis system of induction motors using LabVIEW is proposed to detect the fault of broken rotor bars and shorted turns in stator. This system is not model-based system of induction motor but LabVIEW-based fault diagnosis system using FFT spectrum of stator current in faulty motor without estimating of motor parameters. FFT of stator current in faulty induction motor is measured and compared with various reference fault data in data base to diagnose the fault. This paper is focused on to predict and diagnose of the health state of induction motors in steady state. Also, it can be given to motor operator and maintenance team in order to enhance an availability and maintainability of induction motors. Experimental results are demonstrated that the proposed system is very useful to diagnose the fault and to implement the predictive maintenance of induction motors.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.5
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• pp.414-422
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• 2017

This paper reviews the core technical trends of TESLA EV Motors. The TESLA EV Motors is explosively popular with a considerable recharging infrastructure, a wide 17-[inch] touch display, 417 [HP], and 378 [km] going distance. The object of this study analyzes the body appearance, motor and, battery cooling system, battery arrangement, battery management system, super charging station, power electronics, and induction motor.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1086-1092
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• 2015

The off-line and on-line partial discharge (PD) in the stator winding of three high-voltage (HV) motors (1,400 HP, 6.6 kV) is measured and analyzed in this paper. The off-line PD is measured at high values between 24,300 ~ 36,100 pC after 18 years of motor operation. Spare replacement motors were not available for testing the degree of deterioration of the stator windings in standstill status. Therefore, on-line periodic analysis was conducted to monitor the trend of PD after installing a ceramic sensor (110 pF, 6.6 kV) in the terminal box for each phase of each motor. In the stator winding of the No.1 and No.2 HV motors, which showed high magnitudes of off-line PD and low magnitudes of on-line PD, defects are expected to appear in the neutral end of the winding. On the contrary, in the stator windings of the No.3 HV motor, which exhibits high off-line and on-line PD magnitude, defects are expected to appear in the terminal end of the winding where a voltage close to the phase voltage is applied.

• Journal of Aerospace System Engineering
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• v.16 no.6
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• pp.129-137
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• 2022

Recently, the technology of aircraft drivers has been transitioning from the existing hydraulically-focused mechanical system to an all-electric one due to the high precision and ease of maintenance of electric drivers. Consequently, the failure of an aircraft's electric motor can have fatal consequences. To ensure aircraft safety, efficient and timely fault diagnosis methods are required prompting the active pursuit of research into fault diagnosis technology. This paper introduces and analyses the failure types and failure diagnosis technology trends of permanent magnet synchronous motors among electric motors.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.200-203
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• 2006

Prior to destructive testing, diagnostic tests were performed in eight high voltage motors. Diagnostic tests included polarization index, ac current, dissipation factor($tan{\delta}$) and partial discharge magnitude. The rewind of motor stator insulation at rated voltage is assessed by the results of these tests. After completing the diagnostic tests, the stator windings of motors were subjected to gradually increasing ac voltage, until the insulation punctured. No. 1 motor failed near rated voltage of 12.96 kV. The breakdown voltage of No. 4 motor was 6.99 kV which is lower that expected for good quality coils in 6.6 kV class motors. The failure was located in a line-end coil at the exit from the core slot. These two motors began operation in 1994. While testing No. 7 motor, flashover occurred between the stator winding and the stator frame at 15 kV. The relationship between the diagnostic test and the drop in insulation breakdown voltage was analyzed.

• JOURNAL OF ELECTRICAL WORLD
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• no.6 s.114
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• pp.12-17
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• 1986

• JOURNAL OF ELECTRICAL WORLD
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• no.5 s.113
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• pp.9-13
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• 1986

• Journal of Korean Society for Quality Management
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• v.51 no.2
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• pp.283-296
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• 2023

Purpose: The purpose of this study is to actually implement and verify whether welding defects can be detected in real time by utilizing deep learning AI solutions in the welding process of electric vehicle hairpin winding motors. Methods: AI's function and technological elements using synthetic neural network were applied to existing electric vehicle hairpin winding motor laser welding process by making special hardware for detecting electric vehicle hairpin motor laser welding defect. Results: As a result of the test applied to the welding process of the electric vehicle hairpin winding motor, it was confirmed that defects in the welding part were detected in real time. The accuracy of detection of welds was achieved at 0.99 based on mAP@95, and the accuracy of detection of defective parts was 1.18 based on FB-Score 1.5, which fell short of the target, so it will be supplemented by introducing additional lighting and camera settings and enhancement techniques in the future. Conclusion: This study is significant in that it improves the welding quality of hairpin winding motors of electric vehicles by applying domestic artificial intelligence solutions to laser welding operations of hairpin winding motors of electric vehicles. Defects of a manufacturing line can be corrected immediately through automatic welding inspection after laser welding of an electric vehicle hairpin winding motor, thus reducing waste throughput caused by welding failure in the final stage, reducing input costs and increasing product production.