• Journal of Power Electronics
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• 제12권3호
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• pp.468-476
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• 2012

The interior permanent magnet synchronous motor (IPMSM) has been widely used in electric vehicle applications due to its excellent power to weigh ratio. This paper proposes the maximum torque control of an IPMSM drive using an adaptive learning (AL) fuzzy neural network (FNN) and an artificial neural network (ANN). This control method is applicable over the entire speed range while taking into consideration the limits of the inverter's rated current and voltage. This maximum torque control is an executed control through an optimal d-axis current that is calculated according to the operating conditions. This paper proposes a novel technique for the high performance speed control of an IPMSM using AL-FNN and ANN. The AL-FNN is a control algorithm that is a combination of adaptive control and a FNN. This control algorithm has a powerful numerical processing capability and a high adaptability. In addition, this paper proposes the speed control of an IPMSM using an AL-FNN, the estimation of speed using an ANN and a maximum torque control using the optimal d-axis current according to the operating conditions. The proposed control algorithm is applied to an IPMSM drive system. This paper demonstrates the validity of the proposed algorithms through result analysis based on experiments under various operating conditions.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제55권2호
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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.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권3호
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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 Electrical Engineering and Technology
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• 제12권5호
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• pp.1789-1797
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• 2017

It is necessary to charge electric vehicles in order to drive them. Thus, it is essential to have electric vehicle charging facilities in place. In the case of a household battery charger, the power similar to that consumed by a household with a basic contract power of 3kW is consumed. In addition, many consumers who own an electric vehicle will charge their vehicles at the same time. The simultaneous charging of electric vehicles will cause the load to increase, which then will lead to the imbalance of supply and demand in the distribution system. Thus, a smart charging scheme for electric vehicles is an essential element. In this paper, simulated conditions were set up using real data relating to Korea in order to design a smart charging technique suitable for the actual situation. The simulated conditions were used to present a smart charging technique for electric vehicles that disperses electric vehicles being charged simultaneously. The EVs and Smart Charging Technique are modeled using the Electro Magnetic Transients Program (EMTP).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 B
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• pp.837-839
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• 2001

This paper presents dynamic characteristic of a 2 phase hybrid stepping motor which includes pull-out torque with constant voltage drive and one step response. In order to analyze this characteristics, vector diagram of a synchronous motor and torque-voltage equation are used. Analytic results are good agreement with experimental results.

• 대한기계학회논문집A
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• 제33권5호
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• pp.463-468
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• 2009

Torsional oscillations of the drivetrain in electric vehicles are generated under rapid driving conditions. These lead to an uncomfortable jerking of the vehicle and an increased stress of the mechanical components. To suppress torsional oscillations, the low pass and notch filters between the torque command from the acceleration pedal and electric motor input torque are suggested. The filter parameters are optimized based on Taguchi method with $L_{18}(3^5)$ orthogonal array. The signal to noise (S/N) ratio mainly depends on slew rate of motor input torque, damping ratio and natural frequency of notch filter. With the proposed suppression control scheme, the S/N ratio is shown to be increased by 4.7dB and the torque overshoot of the drive shaft is reduced to 30%.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.135-137
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• 2001

In slotless synchronous motor for precise position and speed control, eccentricity of rotor mass cause torque ripple, speed ripple and harmonics of back emf. This paper deals with magnetic field and characteristic analysis for ring type slotless synchronous motor by using analytical method. And then, speed and back emf harmonics are analysed.

• 전기학회논문지P
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• 제51권4호
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• pp.219-221
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• 2002

This paper presents an electric scooter development using blushless DC motor. In recent scooters was to develop for sport leisure and short transportation. Most of scooter are used petroleum gas. This gas scooter has disadvantage to pollute the air. Some of scooters have developed by DC motor which require a brush. However brushless motors have higher maximum speed and greater capacity, save maintenance labour and produce less noise. There is also greater freedom in planing the usage of brushless motors. In this paper we develop an electric scooter driving BLDC motor for design smart system and control speed of scooter with current reference signal to apply voltage to motor by means of three phase inverter. Using accelerator device we generate current reference to control speed and send the current to a MICOM by A/D converter. This MICOM produces the voltage signal and hall sensors signal and PWM controller drive three phase inverter to minimize error between the reference and an actual current.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2012년도 전력전자학술대회 논문집
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• pp.311-312
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• 2012

Blade pitch control system monitors and adjusts angle of the blades and controls rotation speed of blades. This paper shows 2MW pitch system hardware and electric part. Blade pitch system consists of pitch drive, gear box, motor and energy storage. Fieldbus is base on CANopen protocol. Fail-Safe system moves the blades to a safety position in case of any fault condition. The super capacitor energy storage provides emergency back up to the Pitch servo driver during feathering the blades. This paper studied Blade pitch servo driver and a bi-directional DC-DC converter for fail-safe system.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2012년도 전력전자학술대회 논문집
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• pp.315-316
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• 2012

Three-level neutral point clamping (NPC) converter has been widely applied in high power drive system. And in this paper, a novel method is proposed to realize this algorithm based on FPGA, And the system is consist of two parts, the DSP part and FPGA part, the DSP part includes the control algorithms and the FPGA part works to generate and putout 12 PWM pulses. And the system is tested and verified using both simulation and experimentation.