• Journal of IKEEE
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• v.24 no.3
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• pp.867-876
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• 2020

This paper proposes a neutral-point voltage ripple reduction of high frequency injection sensorless control of IPMSM fed by a three-level inverter. The high frequency voltage injection method has been successfully applied to sensorless control for IPMSM at low speed region. In the process of high frequency voltage injection sensorless control for IPMSM, the neutral-point voltage ripple is increased. It should be reduced because it distorts the output current and decreases a life time of DC-link capacitor. The proposed method in this paper reduces the neutral-point voltage ripple by compensating the reference voltage, and the compensation value is calculated simply with reference voltages and currents. The effectiveness of the proposed method is verified by simulation results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.1
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• pp.40-49
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• 2008

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications and so of due to their excellent power to weight ratio. To obtain maximum efficiency in these applications, this paper proposes the neural network control method. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the error back propagation algorithm(EBPA) of neural network. The minimization of loss is possible to realize eHciency optimization control for the IPMSM drive. This paper proposes high performance and robust control through a real time calculation of parameter variation such as variation of back emf constant, armature resistance and d-axis inductance about the motor operation. Proposed algorithm is applied IPMSM drive system, prove validity through analysis operating characteristics con011ed by efficiency optimization control.

• 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 Power Electronics
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• v.17 no.5
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• pp.401-408
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• 2012

A simple on-line elimination strategy of the dead time and inverter nonlinearity using the current slope information is presented for a PWM inverter-fed IPMSM (Interior Permanent Magnet Synchronous Motor) drive. In a PWM inverter-fed IPMSM drive, a dead time is inserted to prevent a breakdown of switching device. This distorts the inverter output voltage, resulting in a current distortion and torque ripple. In addition to the dead time, inverter nonlinearity exists in switching devices of the PWM inverter, which is generally dependent on operating conditions such as the temperature, DC link voltage, and current. The proposed scheme is based on the fact that the d-axis current ripple is mainly caused by the dead time and inverter nonlinearity. To eliminate such an influence, the current slope information is determined. The obtained current slope information is processed by the PI controller to estimate the disturbance caused by the dead time and inverter nonlinearity. The overall system is implemented using DSP TMS320F28335 and the validity of the proposed algorithm is verified through the simulation and experiments. Without requiring any additional hardware, the proposed scheme can effectively eliminate the dead time and inverter nonlinearity even in the presence of the parameter uncertainty.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1224-1234
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• 2019

Hybrid rotor position estimation methods that integrate a fundamental model and high frequency (HF) signal injection are widely used for the wide speed-range sensorless control of interior permanent-magnet synchronous machines (IPMSMs). However, the direct transition of two different schemes may lead to system fluctuations or system instability since two estimated rotor positions based on two different schemes are always unequal due to the effects of parameter variations, system delays and inverter nonlinearities. In order to avoid these problems, a seamless transition strategy to define and construct a virtual q-axis inductance is proposed in this paper. With the proposed seamless transition strategy, an estimated rotor position based on a fundamental model is forced to track that based on HF signal injection before the transition by adjusting the constructed virtual q-axis inductance. Meanwhile, considering that the virtual q-axis inductance changes with rotor position estimation errors, a new observer with a two-phase phase-locked loop (TP-PLL) is developed to accurately obtain the virtual q-axis inductance online. Furthermore, IPMSM sensorless control with maximum torque per ampere (MTPA) operations can be tracked automatically by selecting the proper virtual q-axis inductance. Finally, experimental results obtained from an IPMSM demonstrate the feasibility of the proposed seamless transition strategy.

• Journal of the Korea Convergence Society
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• v.9 no.4
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• pp.1-7
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• 2018

Electric motors for electric vehicles differ in efficiency characteristics depending on the operation modes, studies for evaluating high efficiency characteristics in low speed and high speed operation modes are very important. Therefore, it is necessary to design method that can change the high torque, high output density, and high efficiency characteristics of driving motors for electric vehicles. In this paper, the diameter ratio of stator and rotor for the interior permanent magnet synchronous motor is change of designed 0.62, 0.65, and 0.68, respectively, and the efficiency characteristics of the entire operation section, average efficiency characteristics of the city driving modes and express highway driving modes are analyzed. As a result of analyzing the efficiency characteristics of the entire operating section, it was confirmed that as the diameter ratio increases, the high efficiency section moves to the low speed and low torque section and the high efficiency section moves to the high speed and low torque neighborhood as the diameter ratio decreases. As a result of analyzing the average efficiency characteristics in the city driving modes and express highway driving modes, the average efficiency of 0.68 model is analyzed to be more efficient than the 0.63 and 0.65 model ratio, and it is confirmed that it is suitable for city driving modes and express highway driving modes.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.361-366
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• 2012

This paper presents speed control of an electric motorcycle using a fuzzy controller. The electric motorcycle required to meet not only fast throttle response but also stability, when it is on a cruise. However, a 1.5KW (50cc) electric motorcycles selling in the current market are difficult to cruise under the following conditions which are occupant's weight, load weight, wind resistance and road conditions (dirt roads, asphalt road). Because of these reasons, the rapid speed changing occurs in uphill and downhill road. To solve these problems, The input value for Improved fuzzy controller use the speed error and error variance. The output value for improved fuzzy controller uses Q-axis of the motor controlled variable. The D-axis of the motor output for improved fuzzy control uses D-axis controlled variable in proportional to Q-axis controlled variable. Improved fuzzy controller drives the electric motorcycle equipped with IPMSM. The control subject used in this paper is a 1.5KW electric motorcycle equipped with improved fuzzy controller that was used to control the motor speed. To control IPMSM Type of motor torque, D, Q-axis current controller was used. The Fuzzy controller using the proposed algorithm is demonstrated by experimental hardware simulator.