• Journal of the Korean Society for Railway
• /
• v.13 no.5
• /
• pp.493-499
• /
• 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.

• Proceedings of the KIEE Conference
• /
• 2008.04c
• /
• pp.119-121
• /
• 2008

This paper is proposed a high Performance speed control of the synchronous reluctance motor through the SV-PWM(Space Vector Pulse Width Modulation) of FAM-PI(Fuzzy Adaptive Mechanism-PI). SV-PWM is controlled using FAM-PI control. SV-PWM can be maximum used maximum do link voltage and is excellent control method due to characteristic to reducing harmonic more than others. Fuzzy control has a advantage which can be robustly controlled. FAM-PI controller is changed fixed gain of PI controller using fuzzy adaptive mechanism(FAM) to match operating condition. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.776_777
• /
• 2009

Optimal efficiency control of synchronous reluctance motor(SynRM) is very important in the sense of energy saving and conservation of natural environment because the efficiency of the SynRM is generally lower than that of other types of AC motors. This paper is proposed a novel efficiency optimization control of SynRM considering iron loss using neural network(NN). The optimal current ratio between torque current and exciting current is analytically derived to drive SynRM at maximum efficiency. This paper is proposed an efficiency optimization control for the SynRM which minimizes the copper and iron losses. The design of the speed controller based on adaptive learning mechanism fuzzy-neural networks(ALM-FNN) controller that is implemented using fuzzy control and neural networks. The objective of the efficiency optimization control is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. The control performance of the proposed controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.20 no.10
• /
• pp.47-57
• /
• 2006

The paper is proposed maximum torque control of SynRM drive using adaptive teaming mechanism-fuzzy neural network(ALM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $^i{_d}$ for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• Proceedings of the KIEE Conference
• /
• 2006.07b
• /
• pp.743-744
• /
• 2006

This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor which minimizes the copper and iron losses. The design of the speed controller based on adaptive fuzzy-neural networks(AFNN) controller that is implemented using fuzzy control and neural networks. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the hybrid artificial intelligent(HAI) controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2009.05a
• /
• pp.416-419
• /
• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under-parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of loaming through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive loaming mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control(FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• Proceedings of the KIEE Conference
• /
• 2005.07b
• /
• pp.1456-1458
• /
• 2005

In this paper, a new approach for the synchronous reluctance motor control which ensures producing maximum torque per ampere(MIPA) over the entire field weakening region is presented. In addition, This paper presents a speed sensorless control scheme of SynRM using artificial neural network. Also, by adjusting the base speed for the field weakening operation according to the flux level, the current and voltage limit, the smooth and precise transition into the field weakening operation can be achieved. The proposed scheme is verified validity through simulation.

• Proceedings of the KIEE Conference
• /
• 2009.04b
• /
• pp.29-31
• /
• 2009

Optimal efficiency control of synchronous reluctance motor(SynRM) is very important in the sense of energy saving and conservation of natural environment because the efficiency of the SynRM is generally lower than that of other types of AC motors. This paper is proposed an efficiency optimization control for the SynRM which minimizes the copper and iron losses. The design of the speed controller based on fuzzy-neural networks (FN)-PI controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization control is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses In variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the proposed controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.23 no.6
• /
• pp.109-117
• /
• 2009

In this paper, an analytical model using equivalent magnetic circuits for the PMA-SynRG is presented. The lumped parameter model (LPM) is developed from machine geometry, stator winding and machine operating specifications. By the LPM, magnetic saturation of rotor bridges is incorporated into model and it provides effective means of predicting machine performance for a given machine geometry. The LPM is not as accurate as finite element analysis but the equivalent magnetic circuits provide fast means of analyzing electromagnetic characteristics of PMa-SynRG. It is the main advantage to find the initial design and optimum design. The initial design of PMa_RSG is performed by LPM model and FEM analysis, and the final PMA-RSG design is optimized and identified by FEM analysis considering actual machine design. The linear LPM and the nonlinear LPM are programmed using MATLAB and all of machine parameters are calculated very quickly. To verify justification of the proposed design of PMa-RSM, back-EMF is measured.