• Journal of Power Electronics
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• v.12 no.3
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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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.3
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• pp.352-357
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• 1996

Recently, Permanent Magnet Synchronous Motor(PMSM) drives are widely used for industrial applications due to its high efficiency and high power factor control strategy. PMSM generally have two classifications such as the SPMSM(Surface Permanent Magnet Synchronous Motors) and IPMSM(Inter Permanent Magnet Synchronous Motors). IPMSA has economical merits over SPMSM in higher speed range, mechanical robustness, and higher power rate by the geometric difference. The maximum torque operation in IPMSM is realized by the current angle control which is to utilize additional reluctance torque due to a rotor saliency. In traction, spindle and compressor drives, constant power operation with higher speed range are desirable. This is simply achieved in the DC motor drives by the reduction of the field current as the speed is increased. However, in the PMSM, direct control of the magnet flux is not available. The airgap flux can be weakened by the appropriate current angle control to demagnetize. In this paper, the control method of optimal current vector in IPMSM is described in order to obtain the maximum torque or maximum output with the speed and load variations. The applied algorithm is realized by the proto system with torque and speed control Experimental results show this approach is satisfied for the high performance servo applications. (author). 6 refs., 9 figs., 1 tab.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.983-984
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• 2011

An effective estimation method of equivalent circuit parameters of three-phase induction motor by using FEM is presented in this paper. Arbitrary three torque-speed points at asynchronous speed on the torque-speed curve are required by using time-stepping FEM, then the equivalent circuit parameters of IM can be calculated rapidly with presented method. After obtaining the equivalent circuit parameters, the general analysis method based on equivalent circuit can be used to get entire torque-speed curve very quickly. Although the purely numerical method such as FEM also can estimate torque-speed curve directly and accurately, however, usually this process is time consuming.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.454-459
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• 1997

The good features of a switched reluctance motor(SRM) are appreciated by the appliance manufactures. And it is spread into a commercial and industries market. The few disadvantage of the motor is higher torque ripple and noise. This paper proposes an instantaneous torque control scheme to control a speed precisely. It adapts phase-locked loop (PLL) technique to control speed precisely. In this control scheme, the phase detector signal of the PLL regulates the switching dwell angle flexibly and the loop filter's signal controls adaptively the instantaneous switching voltage. Experimental results show that drive performance is good with low torque ripple.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.1
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• pp.35-41
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• 2013

Torque characteristics of a turbopump turbine was analyzed using the turbine performance test result. Specific torque of the subject turbine could be expressed as a linear function of corrected rotor speed at a fixed pressure ratio and it has been confirmed by the test result. It also found that corrected rotor speed-specific torque characteristics does not change anymore if the turbine pressure ratio is set bigger than a certain value. Using the turbine torque characteristics and pyro-starter performance test results, rotational speed development behavior of the turbopump was predicted. Prediction revealed that the lap time reaching 50% of turbopump design speed is less than 0.7 second. Effect of the thermal loss between pyro-starter and turbopump was negligible.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.4-10
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• 2012

Torque characteristics of a 75-tonf turbopump turbine was analyzed using the turbine performance test result. Specific torque of the subject turbine could be expressed as a linear function of corrected rotor speed at a fixed pressure ratio and it has been confirmed by the test result. It also found that corrected rotor speed-specific torque characteristics does not change anymore if the turbine pressure ratio is set bigger than a certain value. Using the turbine torque characteristics and pyro-starter performance test results, rotational speed development behavior of the turbopump was predicted. Prediction revealed that the lap time reaching 50% of turbopump design speed is less than 0.7 second. Effect of the thermal loss between pyro-starter and turbopump was negligible.

• 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.

• 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 Advanced Marine Engineering and Technology
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• v.36 no.5
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• pp.694-699
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• 2012

This paper proposes a new sensorless speed control scheme of permanent magnet DC motor using a numerical model and hysteresis controller, which requires neither shaft encoder, speed estimator nor PI controllers. By supplying the identical instantaneous voltage to both model and motor in the direction of reducing torque difference, the rotor speed approaches to the model speed, namely setting value and the system can control motor speed precisely. As the numerical model whose electric parameters are the same as those of the actual motor is adopted, the armature rotating speed can be converged to the setting value by controlling torque on both sides to be equalized. And the hysteresis controller controls torque by restricting the torque errors within respective hysteresis bands, and motor torque are controlled by the armature voltage. The experiment results indicate good speed and load responses from the low speed range to the high, show accurate speed changing performance.

• Wind and Structures
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• v.32 no.2
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• pp.169-177
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• 2021

This study investigates the effects of blade configuration and solidity of Darrieus wind turbine on the starting torque characteristics. Generally, the configuration of Darrieus wind turbine is divided into Troposkien, parabola, Catenary, Sandia, modified-parabola and straight types. A numerical analysis has been carried out using Multiple Stream Tube (MST) method to investigate the effect of blade configuration and solidity of Darrieus wind turbine on the starting torque under the initial low range of rotational speed. The simulation results show that the starting torque of Darrieus wind turbine varies considerably depending on the blade configuration. The initial starting torque was larger with Troposkien, Parabola, Catenary, and Sandia configurations than with modified parabola or straight types. The increase in solidity with increasing number of blades raised the starting torque and improved the dynamic stability during the initial operational speed of Darrieus wind turbine. Additionally, these torque results represent basic data for fluid-structure interaction (FSI) simulation of the steady-dynamic operation of the turbine.