• Proceedings of the KSR Conference
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• 1999.11a
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• pp.99-106
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• 1999

Because many light rail transit systems are mainly operated in the downtown areas of a large cities and the congestion areas, there are many steep gradients and sharp radius sections in that lines. As that reasons above, light rail vehicles are equipped with differential gear units between traction motors and final reduction gear units. In this paper, the configurations and the interferences of 2K-H I type Planetary gear train, which is applicable for light rail vehicles and based on various differential gear units, are studied. The ranges of addendum modification coefficients which would not lead to interferences is analyzed, and optimal addendum modification coefficients among these ranges are presented, which generate the maximum efficiency of planetary gear drives and differential gear unit as pressure angles, speed ratios,

• International Journal of Automotive Technology
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• v.6 no.1
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• pp.23-28
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• 2005

The presented investigation of shift clonk in a vehicle with front-wheel drive shows how a detailed analysis of the complete acoustic system with respect to excitation, transfer and radiation foremost enables possibilities of noise reduction to be worked out. One of the most important basics for the shift clonk analysis was a synchronous measurement of both, torsional vibrations in the drive train on the excitation side as well as airborne and structure-borne noise signals on the transfer and radiation side. Thus, root causes could be identified and improvement measures of the internal shift system could be worked out. An analysis of the transfer paths by means of airborne and structure borne noise measurements made evident that the side shafts were responsible for the disturbing frequencies in the transfer paths. With the help of the FE-simulation it was possible to develop measures of structure optimisation for the side shaft system. The realisation of these measures clearly reduced the shift-noises in the vehicle interior.

• Journal of Power Electronics
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• v.6 no.4
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• pp.279-289
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• 2006

This paper presents a neural network based adaptive dead-time compensation strategy for an inverter fed permanent magnet synchronous motor drive. The neural network is used for identifying the dead-time compensation time (DTCT) that includes an equivalent dead-time, turn-on/off time and on-state voltage components of the voltage source inverter. In order to train the neural network, desired DTCTs for eight operating points are prepared as training data. The trained neural network can identify a desired DTCT for any operating point because it has the capability of the interpolation. The accuracy of the identified DTCT is experimentally confirmed by comparing the calculated active power with a measured one.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.207-214
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• 2014

If two or more Permanent Magnet Synchronous Motors (PMSM) can be controlled by one inverter, a train can be driven by less energy than the present Induction Motor (IM) drive system. First, this paper proposes a method for simulating the movement of wheels and a vehicle to develop a control method. Next, a method is presented for controlling two or more PMSMs by one inverter.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.289-291
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• 1996

Linear induction motor(LIM) is widely used to drive magnetic levitation train. To drive LIM, different control method compared with conventional rotary type machine is needed. Since vertical force is generated inherently and it effects on the levitation system, vertical force should be kept constant for stable levitation. To keep vertical force constant, slip frequency should be kept constant. Once slip frequency is kept constant, tractive force can be controlled by adjusting motor currents. In this paper, control methods used so far arc analyzed with some experimental results and decoupling control algorithm is proposed to control tractive and vertical force separately. Control algorithm is verified through simulation.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.141-143
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• 2008

Due to the demand for high-output motors in the limited space between the wheels in an electric train, self-ventilating traction motors have been used for many years. periodical disassembly maintenance is necessary to remove the small quantities of dust that enter the motor from the open-air ventilation. Reducing this burden, as well as increasing efficiency and reducing noise, would benefit the next generation of moters To address these needs, KRRI is developing a fully enclosed type traction motor, a fully enclosed type traction motor with outer fans, a high-efficiency permanent-magnet synchronous motor and a direct-drive motor(DDM) as traction motors for the next generation of trains.

• Journal of Power System Engineering
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• v.2 no.3
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• pp.74-82
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• 1998

This paper presents a new approach to the design of speed and azimuth control of a mobile robot with two drive wheels. The proposed control scheme uses a Gaussian function as a unit function in the neural-fuzzy network and back propagation algorithm to train the neural-fuzzy network controller in the framework of the specialized learning architecture. It is proposed to a learned controller with two neural-fuzzy networks based on an independent reasoning and a connection net with fixed weights to simplify the neural-fuzzy network. The performance of the proposed controller can be seen by the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of Ocean Engineering and Technology
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• v.11 no.1
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• pp.84-95
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• 1997

This paper presents a new approach to the design speed and azimuth control of a mobile robot with drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the frmework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simple the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.237-240
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• 2000

본 논문에서는 ISM(Industrial Scientific Medical) 대역 424MHz부터 429MHz까지의 범위에서 동작하는 열차 후부 감시제어 시스템용 RF 전력증폭기를 설계 및 제작하였다. 424MHz대역에서의 2W급 대전력 증폭기의 설계방법으로는 Double Stub Tuner구조를 이용하여 최적 부하 임피던스를 추출하는 방법을 제시하였고, 초고주파 시뮬레이터인 Serenade8.0을 사용하여 Drive_amp와 LPF를 설계하였다. 제작된 Drive_amp와 LPF의 성능 및 특성은 시뮬레이션 한 결과와 거의 일치하였으며, 대전력 증폭기의 측정결과로는 추출하고자 하는 출력 레벨인 33㏈m을 얻을 누 있었고, 원신호의 Hamonic 주파수 성분과는 40.34㏈c의 결과를 보임으로써 안정된 전력증폭기를 구현하였다.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1050-1052
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• 1996

This paper presents a neuro-control algorithm for the speed control of a direct drive motor without the knowledge of the dynamics of the motor and the characteristics of a nonlinear load. In the field of motor control, it is not possible to directly use the back-propagation method in order to train a network since the desired output of the network is not known. Hence, we propose an extended back-propagation algorithm to force the closed loop system to give desired results. Experimental results shown that the proposed neuro-controller can reduce the unknown load effects and have the good velocity tracking capabilities.