• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.3
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• pp.110-114
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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. In this paper maximum torque control of IPMSM drive using artificial intelligent(AI) controller is proposed. 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 adaptive learning mechanism fuzzy neural network(ALM-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 ALM-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 Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.8
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• pp.85-93
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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 posed maximum torque control of IPMSM for high speed drive. 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 IPMSM drive system for high speed drive, the operating characteristics controlled by maximum torque control are examined in detail by experiment.

• Journal of the Korean Society for Railway
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• v.15 no.4
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• pp.376-380
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• 2012

A study on the iron-loss reduction of 110kW-class Interior Permanent Magnet Synchronous Motor (IPMSM) for Light Railway Transit (LRT) is conducted. In general, the iron loss of IPMSM depends on the characteristics of core material and non-oriented electrical steel is used as a core material of IPMSM. In order to reduce the iron-loss of IPMSM, both non-oriented electrical steel and grain oriented electrical steel are applied as core material. Iron loss of 110kW-class IPMSM can be reduced approximately 40% comparing to an existing IPMSM by applying grain oriented electrical steel to the stator teeth.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.3
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• pp.279-287
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• 2010

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 efficiency optimization control of IPMSM drive using adaptive fuzzy learning controller(AFLC). 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 design of the current based on adaptive fuzzy control using model reference and the estimation of the speed based on neural network using ANN controller. 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. Also, this paper proposes speed control of IPMSM using AFLC1, current control of AFLC2 and AFLC3, and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled AFLC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1475-1480
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• 2013

In this paper, the basic design study of a water-cooling jacket, which have reported no cases for applying to railway traction motors so far, were conducted for applying to Interior Permanent Magnet Synchronous Motor (IPMSM) for railway vehicles. The basic thermal characteristics analysis of the 110kW-class IPMSM was performed by using 3-dimentional thermal equivalent network method. The necessary design requirements of the water-cooling jacket were derived by analyzing the results of the basic thermal properties. Next, the thermal characteristics analysis technique was established by using the equivalent model of the solenoid-typed pipe to be installed on the inside of the water-cooling jacket for 110kW-class IPMSM. Finally, a design model of 6kW-class water-cooling jacket was derived through the analysis of various design parameters.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.853-854
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has higher power density than other PM(permanent Magnet) machines due to reluctance torque in addition to magnetic torque, and the ratio of magnetic and reluctance torque has influences on motor characteristics such as input current, efficiency, power factor, etc. Therefore, this paper presents the output characteristics of IPMSM according to the ratio magnetic and reluctance torque of IPMSM and discuss the design strategy of IPMSM.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.104-105
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• 2013

When actual IPMSM is driving, it is difficult to figure out the correct current during the current control period due to the operation speed limit of digital signal processing. Therefore, in order to control IPMSM for electric vehicle efficiently, we should design 2D Look-up Table to find out optimal current reference corresponding to speed and torque of IPMSM. This paper explains the design method of 2D Look-up Table for optimal current control of constant torque area and constant output area of IPMSM for electric vehicle. Finally, experimental results are presented to verify the reliability of 2D Look-up Table.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.12
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• pp.697-703
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• 2002

Interior permanent magnet synchronous motor(IPMSM) is widely used in many applications such as an electric vehicle, compressor drives of air conditioner and machine tool spindle drives. In order to maximize the efficiency in such applications, this paper is proposed 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. The proposed control algorithm is applied to IPMSM drive system, the operating characteristics controlled by efficiency optimization control are examined in detail by simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.293-300
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• 2011

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 and adaptive fuzzy learning contrroller(AFLC) for speed control in IPMSM Drives. AFLC is chaged fuzzy rule base by rule base modifier for robust control of IPMSM. 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 and AFLC is confirmed by comparing to conventional algorithm.

• Journal of Power Electronics
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• v.9 no.1
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• pp.117-123
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• 2009

This paper presents a sliding mode observer for the sensorless control of interior permanent magnet synchronous motor (IPMSM) drives. The sliding mode observer has been presented as a robust estimation method. Most of these previous works, however, were not for an interior PMSM (IPMSM), but for a non-salient pole PMSM and its observer design is conducted in the stationary reference frame. Thus, in this paper, we investigate the design of a sliding mode observer and its driving characteristics for an IPMSM. The proposed sliding mode observer is designed in the rotating reference frame, and good drive performance is achieved even when the observer parameters are mismatched with those of an actual motor. The proposed method is applied to a 600W IPMSM, and, then, the measurement results are presented.