• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1356-1357
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• 2011

Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. This paper proposes on-line efficiency optimization of IPMSM drive using fuzzy logic control(FLC) and the loss minimization method. In order to optimize the efficiency the loss minimization algorithm is developed based on motor model and operating condition. The d-axis armature current is utilized to minimize the losses of the IPMSM in a closed loop vector control environment. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The optimal current can be decided according to the operating speed and the load conditions. The proposed control algorithm is applied to IPMSM drive system and the operating characteristics controlled by the loss minimization method and FLC control are examined in detail.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.2
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• pp.74-82
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• 2007

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 efficiency optimization control of IPMSM drive using adaptive fuzzy learning control fuzzy neural network (AFLC-FNN) controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AFLC-FNN controller. Also, this paper proposes speed control of IPMSM using AFLC-FNN and estimation of speed using ANN controller. 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 AFLC-FNN controller, the operating characteristics controlled by efficiency optimization control are examined in detail.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2411-2418
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• 2017

This study focuses on the effects of using open stator slots in an interior permanent magnet traction motor with a magnetic slot wedge design in order to increase the power density at its base speed. In addition, such a configuration reduces the torque ripple under field-weakening conditions. Five different wedge models were selected, each of which was evaluated using a finite element analysis (FEA). Based on the initial model, we designed magnetic slot wedges for maximum back-EMF and minimum cogging torque. In addition, the d-q axis inductance was slightly altered due to the magnetic slot wedges. Finally, we analyzed the performance of a traction machine under field weakening control. Moreover, we have outlined the requirements for an ideal magnetic slot wedge design.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.310-313
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• 2003

This paper is proposed new fuzzy controller for high performance of interior permanent magnet synchronous motor (IPMSM) drive New fuzzy controller take out appropriate amounts of accumulated control input according to fuzzy described situations in addition to the incremental control input calculated by conventional direct fuzzy controller. The structures of the proposed controller is motivated by the problems of direct fuzzy controller. The direct controller generally give inevitable overshoot when one tries to reduce rise time of response especially when a system of order higher than one is under consideration. The undesirable characteristics of the direct fuzzy controller are caused by integrating operation of the controller, even though the integrator itself is introduced to overcome steady state error in response. Proposed controller fuzzy clear out integrated quantities according to situation. This paper attempts to provide a thorough comparative insight into the behavior of IPMSM drive with direct and new fuzzy speed controller. The validity of the comparative results is confirmed by simulation results for IPMSM drive system.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.6
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• pp.573-578
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• 2013

In the case of the Back EMF voltage contains the harmonics, the motor torque ripple and vibration is occurred by the current pulsation, because IPMSM control algorithm is the model which is assumed that it contains a sinusoidal Back EMF voltage. To improve ride quality, in the case of IPMSM for EV, improving the torque control characteristics is necessary. Therefore, there is a need to minimize the influence of the harmonics. In this paper, the investigation to decrease the current distortion factor has been performed for improving torque control characteristics by applying the non-sinusoidal Back EMF to IPMSM model.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1056-1061
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• 2013

The widely used motors in HEV(Hybrid Electric Vehicles) are IPMSM(Interior Permanent Magnet Synchronous Motor) which has no rotor heat, higher efficiency and advantageous in volume and weight comparing with other motors. For vector control of IPMSM, position information of rotor is required but Resolver is mainly used as the detecting sensor. However, the use of position sensors will reduce the system reliability of hybrid electric vehicles. In this paper, a way to control the motor by sensorless was proposed at the event of sensor failure. We also implemented IPMSM sensorless operation by the expanded EMF(Electro Motive Force) voltage way and harmonic voltage which is applying in the low speed area. And we proposed how to change with sensorless control by detecting the position sensors failure and verified it through experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1700-1707
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• 2011

Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. Since the fuzzy neural network(FNN) is recognized general approximate method to control non-linearities and uncertainties, the development of FNN control systems have also grown rapidly. The FNN controller is compounded of fuzzy and neural network. It has an advantage that is the robustness of fuzzy control and the ability to adapt of neural network. However, the FNN has static problem due to their feed-forward network structure. This paper proposes high performance speed control of IPMSM drive using the recurrent FNN(RFNN) which improved conventional FNN controller. The RFNN has excellent dynamic response characteristics because of it has internally feed-back structure. Also, this paper proposes speed estimation of IPMSM drive using ANN. The proposed method is analyzed and compared to conventional FNN controller in various operating condition such as parameter variation, steady and transient states etc.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1851-1863
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• 2017

Interior permanent magnet synchronous motor (IPMSM) is most commonly used in the automotive industry as a traction motor for electric vehicle (EV). In electric vehicle, the torque output rapidly changes according to the operation of the accelerator and the braking of the driver. The transient torques are thus generated very frequently in accordance with the variable speed control of the driver. Therefore, in this paper, a method for improving the torque response in the transient states of IPMSM is proposed. In order to complement the disadvantages of the conventional PI current controller in the field oriented control (FOC), the finite-state model predictive current control and 2D-LUT is applied to improve the torque response at the torque transient period. Simulation and experiment results are given to verify the reliability of the proposed method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.12
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• pp.9-20
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• 2012

This paper proposes the efficiency optimization control of interior permanent magnet synchronous motor(IPMSM) drive using series connected-fuzzy neural network PI(SC-FNPI) controller. The PI controller is generally used to control IPMSM drive in industrial field. However, the PI controller has problem which is falling control performance about parameter variation such as command speed, load torque and inertia due to fixed gain of PI controller. Therefore, to improve performance of PI controller, this paper proposes SC-FNPI controller adjusted input of PI controller by FNN controller according to operating conditions. Also, this paper proposes efficiency optimization control which is improving efficiency with minimize loss. The SC-FNPI controller proposed in this paper is compared control performance with conventional FNN and PI controller about command speed, load torque and inertia variation. And the efficiency optimization control is compared with $i_d=0$ control about loss and efficiency. The SC-FNPI controller proposed in this paper shows more excellent control performance for rising time, overshoot and steady-state error. Also efficiency optimization control is increased efficiency by reducing loss.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.7
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• pp.15-25
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• 2011

This proposes an online loss minimization algorithm for series PI(SPI) based interior permanent magnet synchronous motor(IPMSM) drive to yield high efficiency and high dynamic performance over wide speed range. The loss minimization algorithm is developed based on the motor model. In order to minimize the controllable electrical losses of the motor and thereby maximize the operating efficiency, the d-axis armature current is controlled optimally according to the operating speed and load conditions. For vector control purpose, a SPI is used as a speed controller which enables the utilization of the reluctance torque to achieve high dynamic performance as well as to operate the motor over a wide speed range. Also, this paper proposes current control of model reference adaptive fuzzy controller(MFC), and estimation of speed using artificial neural network(ANN) controller. The proposed efficiency optimization control, SPI, MFC, ANN in this paper is applied to IPMSM drive system, the validity of this paper is proved by analyzing response characteristics in variety operating conditions.