• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.664-669
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• 1992

In this paper, we present a DSP-based high dynamic performance torque control scheme of variable reluctance motors(VRM's) for DD(Direct Drive) robots via function inversion technique. The VRM with our controller behaves like DC motors, and hence developed torque tracks given torque command accurately with no torque ripples. Furthermore, our torque control algorithm ensures the production of maximum constant torque under maximum current limitation, minimizes power loss in each phase resistance, and takes magnetic saturation effect into account. Also, since our control algorithm is represented in the form of look-up table, it can be easily implemented with simple digital circuits and this tabular design method is computationally more accurate and simpler compared to the prior methods.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1262-1270
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• 2010

The next generation domestic high speed railway system is a power dispersed type and uses vector control method for motor speed control. Nowadays, inverter driven induction motor system is widely used. However, recently PMSM drives are deeply considered as a alternative candidate instead of an induction motor driven system due to their advantages in efficiency, noise reduction and maintenance. In this paper, the maximum torque control approach is presented for the IPMSM drives with reluctance torque. The applied control method uses maximum torque control per ampere technique. Simulation programs based on Matlab/Simulink are developed. Finally the designed system is verified by simulation and their characteristics are analyzed by the simulation results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.584-593
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• 2018

The highly efficient operation of induction motors has been studied in the past years. Among the many attempts made to obtain highly efficient operation, Maximum Torque Per Amp (MTPA) controls in induction motor drives were proposed. This method enables induction motor drives to operate very efficiently since it achieves the desired torque with the minimal stator current. This is because the alternate qd induction motor model (AQDM) is a highly accurate mathematical model to represent the dynamic characteristics of induction motors. However, it has been shown that the variation of the rotor resistance degrades the performance of the MTPA control significantly, thus leading to its failure to satisfy the maximum torque per amp condition. To take into consideration the mismatch between the actual value of the rotor resistance and its parameter value in the design of the control strategy, an adaptive MTPA control was proposed. In this work, this adaptive MTPA control is investigated in order to achieve the desired torque with the minimum stator current at multiple operating points. The experimental study showed that (i) the desired torque was accurately achieved even though there was a deviation of the order of 5% from the commanded torque value at a torque reference of 25 Nm (tracking performance), and (ii) the minimum stator current for the desired torque (maximum torque per amp condition) was consistently satisfied at multiple operating points, as the rotor temperature increased.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.103-105
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• 2009

This paper presents the maximum-power control simulation for PMA-SynRM. For maximum power, the maximum torque / current control method is conducted in constant-torque range and flux-weakening control method is conducted in constant-power range. For considering the nonlinear characteristics of inductance, machine constant is determined by FEM. Finally, experiment is conducted to calculate the efficiency.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.3
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• pp.240-245
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• 2004

This paper presents a Switched Reluctance Motor(SRM) drive using the self-tuning control method to achieve the maximum torque. SRM has the difficulty to research it by an analytic method and to control the speed End torque because of the high nonlinearity. So, in this paper, the self-tuning control method is applied to relevantly controlling turn-on/off angle to operate at the maximum torque. Also, the feedback signals to control the turn-on/off angle are the encoder pulse and the increment of phase current. At first, n adequate turn-off angle is searched by itself and then a turn-on angle is done. As the relationship between turn-on and him-off angle is mutual dependent, the turn-on/off angle is controlled by a real time self-tuning control method in order to maintain the maximum torque. The proposed self-tuning Algorithm is verified by experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3110-3114
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• 2009

Rotor temperature variation is a significant issue in the design of induction motor controls. In the literature, numerous studies have mentioned significant performance degradation due to rotor temperature variation unless it is taken into account. However, those studies have mainly focused on field-oriented control in terms of tracking performance. There was little research about the influence of rotor temperature variation on performance particularly in the case of optimal controls such as maximum torque per amp (MTPA) control strategy. This work investigates how to affect the performance of maximum torque per amp (MTPA) control strategy as rotor temperature varies in time. To this end, investigation was carried out in two ways to see whether the objective of MTPA control strategy is achieved regardless of rotor temperature variation. It is to produce a desired torque with the minimum possible stator current at the same time. Laboratory experiment shows that tracking performance and maximum torque per amp condition is significantly affected by rotor temperature variation as rotor temperature varies, thus ending up with performance degradation of MTPA control.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.87-91
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• 2005

A conceptual design for the movable roll vane system is done for the roll stability control of KSLV-I. The control effectiveness of the roll vanes is estimated using the numerical simulation. The hinge location is selected to minimize the torque requirement at the maximum dynamic pressure condition, and the maximum torque of 3.0 kN-m is found to be required to actuate the roll vanes for the entire range of operation. An electro-mechanical actuator system which is composed of a DC motor, the speed reducers, the battery package and the controller is designed using the given requirements, the maximum torque of 3.0 kN-m, the maximum deflection angle of 25 deg. and the maximum angular velocity of 30 deg/sec. More detailed design to make more compact and highly efficient system will be done in the future.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.297-299
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• 2002

This paper is proposed maximum torque control for electric vehicle drive. At low speeds, the reluctance torque is used to maximize the output for a given current level. This Is achieved maximum torque per ampere(MTPA) by selecting an optimal value of the direct stator current component. At high speeds, the system reaches a point at which the inverter will not be able to supply the desired voltage In this case it Is necessary to make use of an increased value the direct current component. The proposed control algorithm is applied to PMSM drive system, the operating characteristics controlled by maximum torque control are examined in detail by simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1142-1151
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• 2015

In this paper, High performance torque control based on the flux mapping of 48V Wound Rotor Synchronous Motor has been studied to improve torque control. Flux map considering MTPA (Maximum Torque Per Ampere), MFPT (Minimum Flux Per Torque), Maximum efficiency point at the same torque command and flux command for each field current was produced. Current map using flux mapping of Each field current was applied to the MTPA, MFPT. Generating a current vector locus was to determine the characteristics of the operation region. Through the Matlab/Simulink simulation, difference between speed-torque map and flux map was represented. The suggested flux map was tested actual experiments on a dynamometer.