• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.4
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• pp.279-285
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• 2020

An open-end winding (OEW) permanent magnet synchronous motor with dual inverters can synthesize large voltages for a motor with the same DC link voltage. This ability has the advantage of reducing the use of DC/DC boost converters or high voltage batteries. However, zero-sequence voltage (ZSV), which is caused by the difference in the combined voltage between the primary and secondary inverters, can generate a zero-sequence current (ZSC) that increases system losses. Among the methods for eliminating this phenomenon, combining voltage vector eliminated ZSV cannot be accomplished by the conventional Pulse Width Modulation(PWM) method. In this study, a PWM carrier generation method using functionalization to generate a switching pattern to suppress ZSC is proposed and applied to analyze the control influence of the center-zero vector in the switching sequence about the current ripple.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2503-2508
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• 2005

In this paper, we propose a new discrete-time predictive current controller for a PMSM(Permanent Magnet Synchronous Motor). The main objectives of the current controllers are to ensure that the measured stator currents tract the command values accurately and to shorten the transient interval as much as possible, in order to obtain high-performance of ac drive system. The conventional predictive current controller is hard to implement in full digital current controller since a finite calculation time causes a delay between the current sensing time and the time that it takes to apply the voltage to motor. A new control strategy in this paper is seen the scheme that gets the fast adaptation of transient current change, the fast transient response tracking. Moreover, the validity of the proposed method is demonstrated by numerical simulations and the simulation results will present the improvements of predictive controller and accuracy of the current controller.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.566-569
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• 2005

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using artificial intelligent(AI) controller. 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. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using learning mechanism fuzzy neural network(LM-FNN) and estimation of speed using artificial neural network(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 LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also. this paper is proposed the experimental results to verify the effectiveness of AI controller.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.3
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• pp.39-46
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for the speed control of interior permanent magnet synchronous motor(IPMSM) drive. The design of this algorithm based on FNN controller that is implemented by using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights among the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strongly high performance and robustness in parameter variation, steady-state accuracy and transient response.

• Journal of IKEEE
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• v.24 no.2
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• pp.441-445
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• 2020

A Permanent Magnet Synchronous Motor (PMSM) for an electrical power steering system (EPS) is adopting various dual three-phase type stator windings to get the high fault tolerance capability when the motor runs at the failure condition. In this paper, we analyze the effects of stator winding arrangements on the characteristics such as torque and efficiency of the PMSM with leading and lagging current angle variations using finite element method. As a result, the most valuable design criteria are proposed to select stator winding method. Especially, we suggest the most appropriate winding method in terms of torque and efficiency, extending constant output area and decreasing noise and torque ripples.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.707-708
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• 2008

본 논문에서는 초전도 플라이휠 에너지 저장장치 (Superconductor Flywheel Energy Storage System : SFES)의 에너지 변환을 위해 사용된 영구 자석형 전동 발전기(Permanent Magnet Synchronous Motor/Generator : PMSM/G)가 SFES의 에너지 저장효율에 미치는 영향을 평가하였다. SFES 시스템은 YBCO 벌크 초전도체를 이용한 저어널 타입(journal type)의 초전도 베어링을 사용하였으며, 슬롯리스 형 PMSM/G를 사용하였다. PMSM/G의 고정자 코어, 누설 자속 및 감겨진 코일에 의한 저장 에너지 손실을 측정하였다. 사용된 코어의 크기, 누설자속, 및 코일의 적절한 선정을 통하여 저장된 에너지의 손실을 상당히 줄일 수 있음을 확인하였다. 또한 영구자석과 코어가 동시에 회전하는 회전 코어형 전동발전기를 적용하여 에너지 손실을 매우 감소시킬 수 있음을 확인하였다.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.97-105
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• 2013

The control method of the bidirectional DC/DC converter for instantaneous regenerative current control is described in this paper. The general method to control the DC/DC converter is the output voltage control. However, the regenerative current cannot be controlled to be constant with this control method. To improve the performance of the conventional control method, the DC-link voltage of the inverter is controlled within the tolerance range by the instantaneous boost and buck operations of the bidirectional DC/DC converter. By the proposed control method, the battery current can be controlled to be constant regardless of the motor speed variation. The improved performance of the DC/DC converter controlled by the proposed control method is verified by the experiment and simulation of the system with the inverter and IPMSM(Interior Permanent Magnet Synchronous Motor) which is operated by the reduced practical speed profile.

• Journal of Power Electronics
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• v.11 no.4
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• pp.527-532
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• 2011

Due to the need for improved fuel consumption and the trend towards increasing the electrical content in automobiles, integrated starter generator (ISG) systems are being considered by the automotive industry. In this paper, in order to change the conventional generator of a vehicle, a belt driven integrated starter generator is considered. The overall ISG system, the design considerations for the claw pole type AC electric machine and a low voltage very high current power stage implementation are discussed. Test data on the low voltage claw pole type machine is presented, and a large current voltage source DC/AC inverter suitable for low voltage integrated starter generator operation is also presented. A metal based PCB (Printed Circuit Board) power unit to attach the 4-parallel MOS-FETs is used to achieve extremely high current capability. Furthermore, issues related to the torque assistance during vehicle acceleration and the generation/regeneration characteristics are discussed. A prototype with the capability of up to 1000 A and 27 V is designed and built to validate the kilo-amp inverter.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.89-97
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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. The paper is proposed maximum torque control of IPMSM drive using learning mechanism-fuzzy neural network(LM-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. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using LM-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using LM-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 LM-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 LM-FNN and ANN controller.