• Steel and Composite Structures
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• v.24 no.4
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• pp.399-408
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• 2017

Of high strength bolts, the torque shear type bolt is known to be clamped normally when pin-tails are broken. Sometimes the clamping loads on slip critical connections considerably fluctuate from the required tension due to variation of torque coefficient. This is why the viscosity of lubricant affects the torque coefficient by temperature. In this study, the clamping tests of high strength bolts were performed independently at laboratory conditions and at outdoor environment. The temperatures of outdoor environment candidates were ranged from $-11^{\circ}C$ to $34^{\circ}C$ for six years. The temperature at laboratory condition was composed from $-10^{\circ}C$ to $50^{\circ}C$ at each $10^{\circ}C$ interval. At outdoor environment conditions, the clamping load of high strength bolt was varied from 159 to 210 kN and the torque value was varied from 405 to 556 Nm. The torque coefficients at outdoor environment were calculated from 0.126 to 0.158 when tensions were measured from 179 to 192 kN by using tension meter. The torque coefficients at outdoor environment conditions were analyzed as the range from 0.118 to 0.152. From these tests, the diverse equations of torque coefficient, tension dependent to temperature can be acquired by statistic regressive analysis. The variable of torque coefficient at laboratory conditions is 0.13% per each $1^{\circ}C$ when it reaches 2.73% per each $1^{\circ}C$ at outdoor environment conditions. When the results at laboratory conditions and at outdoor environment were combined to get the revised equations, the change in torque coefficient was modified as 0.2% per each $1^{\circ}C$ and the increment of tension was adjusted as 1.89 % per each $1^{\circ}C$.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.99-104
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• 2008

The Carbon fiber epoxy composite material and aluminum have many advantages about higher specific stiffness and good fatigue characteristics. basically, the propeller shaft of automobile must satisfy high natural frequency more than 9,200 rpm to satisfy high number of rotation and high torsion torque more than 2,700Nm. In these reason, studied natural frequency and torsion torque characteristics of shaft according to parameter variations with the outdiameter and thickness. From the torsion tester and natural frequency experiments FE analyses was compared vibration and torque characteristics of hybrid shaft Designed hybrid shaft was experimented through FFT analyzer and torsion tester each and satisfied that hybrid shaft reverence 60mm and thickness 5mm by a these experiment is most suitable. Therefore, that can manufacture existent steel two piece type propeller shaft to one piece type hybrid shaft.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.5
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• pp.332-337
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• 2004

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 the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.12
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• pp.156-163
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• 2010

The brushless motor is getting widely applied to the automotive component with the advantage of the high efficiency, high reliability and etc.. Most of the motor applications require the low vibration and acoustic noise. The cogging torque is the one of the main cause of the noise and vibration. The step-skewed rotor is used to reduce the cogging torque. We analyze the characteristics of the step-skewed rotor and non skewed rotor with the same stator by using 2-dimensional FEM. And then we analyze the characteristics variation according to the rotor eccentricity. The prototype is made and tested. As the results, the step-skewed rotor structure reduce the cogging torque and local radial force but it is more sensitive to rotor eccentricity.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.165-170
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• 2015

In this paper, The strength and driving characteristics of it were investigated according to developing the traction motor for 8200 electric locomotive series. For this purpose, Flux density strength was analyzed and then structural strength was investigated such as a stator frame, design of the rotor shaft bearing according to the design process. In addition, the traction motor operating point was analyzed according to slip frequency variation at a power source frequency. As the results of analysis on torque-speed characteristic curve, we was confirmed that traction motor was controlled as torque control prior to motor speed 1610[rpm], power control between 1610[rpm] and 2500[rpm] and breakdown torque control more than motor speed 2500[rpm].

• 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.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.824-827
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• 2003

Recently, Development of Rare Earth Permanent magnet with the high remanence, high coercivity allow the design of brushless motors with very high efficiency over a wide speed range. Cogging torque is produced in a permanent magnet by magnetic attraction between the rotor mounted permanent magnet and the stator teeth. It is an undesired effect that contributes to the machines output ripple, vibration, and noise. This cogging torque can be reduced by variation of magnet arc length, airgap length, magnet thickness, shifting the magnetic pole and varying the radial shoe depth and etc. In this paper, Some airgap length and magnet arc that reduce cogging torque are found by FEM(Finite element method). The SPM type of high-capacity BLDC motor is optimized as a sample model.

• Journal of Electrical Engineering and Technology
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• v.5 no.3
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• pp.462-467
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• 2010

This paper presents the rotor shape optimization of an interior type permanent magnet (IPM) motor for a reduction of vibration and Electromagnetic Interference (EMI). The vibration and EMI in permanent magnet motors is generated by cogging torque ripple, radial force and commutation torque ripple. Consequently, in order to improve vibration and EMI, the optimal notches are put on the rotor pole with an arc shape proposed. The variation of vibration frequency due to the cogging torque and radial force of each model is computed by the finite element method (FEM). From the analysis result and experiment, we confirmed the proposed model has remarkably improved the vibration and EMI.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.69-75
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• 2006

This paper deals with the optimum design solution on reduction of torque ripple for a Synchronous Reluctance Motor with concentrated winding using response surface methodology. The coupled Finite Elements Analysis (FEA) & Preisach model have been used to evaluate the nonlinear solution. Comparisons are given with characteristics of a SynRM according to the stator winding, slot number, open width of slot, slot depth, teeth width variation in concentrated winding SynRM, respectively. This paper presents an optimization procedure using Response Surface Methodology (RSM) to determine design parameters for reducing torque ripple. RSM has been achieved to use the experimental design method in combination with finite Element Method (FEM) and well adapted to make analytical model for a complex problem considering a lot of interaction of design variables. Moreover, Sequential Quadratic Problem (SQP) method is used to solve the resulting of constrained nonlinear optimization problem.