• 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 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 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.3
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• pp.430-438
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• 2019

For a pump or a compressor motor, a high periodic load torque variation is induced by the mechanical works, and it causes system vibration and noise. To minimize these problems, load torque compensation method, injecting periodic torque current, could be utilized. However, with the sensorless control method, which is usually utilized in the pump and compressor for low cost, the periodic torque current degrades the accuracy of the rotor position estimation owing to the inductance variation. This paper analyzes the rotor position and speed estimation error of sensorless control method with constant motor parameters under period loading. Assuming the constant speed by the accurate load torque compensation, the speed error equation is derived in frequency domain with inductance depending on the stator current. Further, it is also shown that the rotor position error could be minimized by compensating the inductance variation. The simulation and experimental results verify that the derived speed error model and the validity of the inductance compensation method.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.2
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• pp.139-147
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• 2004

The purpose of engine control TCS is to regulate engine torque to keep driven wheel slip in a desired range. In this paper, engine control TCS using sliding mode control law based on engine model and estimated load torque is proposed. This system includes a two-level controller. Slip controller calculates desired wheel torque, and engine torque controller determines throttle angle for engine torque corresponding to desired wheel torque. Another issue is to measure load torque for model based controller design. Luenberger observer with state variables of load torque and engine speed solves this problem as estimating load torque. The performance of controller and observer is certificated by simulation using 8-degree vehicle model, Pacejka tire model, and 2-state engine model. The simulation results in various maneuvers during slippery and split road conditions showed that acceleration performance and ability of the vehicle with TCS is improved. Also, the load torque observer could estimate real load torque very well, so its performance was proved.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.4
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• pp.377-382
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• 2012

This paper presents a proof-of-concept study on the evaluation of torsional vibration isolation performance through in-situ output torque measurement by using a non-contacting magneto-elastic torque transducer installed in the vehicle driveline system. The de-trending processing is first conducted to extract the torsional vibration from the measured driveline output torque. In order to estimate the transmissibility, primary performance indicator of a vibration isolator, the magnitude of transmitted torsional vibration with different frequencies is compared. From the conservative estimation results, the torsional damper built in a lock-up clutch of a torque converter is identified to be a vibration isolator. The evaluation results show that the fluid damping by torque converter outperforms the vibration isolation function of a torsional damper, and the isolation performance needs to be enhanced.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.10
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• pp.789-796
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• 2016

The weight of an antenna system pointing satellite on the mobile platform is restricted by the weight limit of the mobile platform. The maximum power of the actuator driving the antenna system is thus limited because a high power actuator needs a heavier weight. Thus, a drive system is designed to have a low torque requirement by reducing the gravitational torque depending on gravity or acceleration of the mobile platform, including vibration, shock, and accelerated motion. To reduce the gravitational torque, the mathematical model of the gravitational torque is preferentially obtained. However, the method to directly estimate the mathematical model in an antenna system has not previously been reported. In this paper, a method is proposed to estimate the gravitational torque as a mathematical model in the antenna system. Additionally, a method is also proposed to calculate the optimal weight of the balancing weight to compensate for the gravitational torque.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.382-387
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• 2012

This paper presents a proof-of-concept study on the evaluation of torsional vibration isolation performance through in-situ output torque measurement by using a non-contacting magneto-elastic torque transducer installed in the vehicle driveline system. The de-trending processing is first conducted to extract the torsional vibration from the measured driveline output torque. In order to estimate the transmissibility, primary performance indicator of a vibration isolator, the magnitude of transmitted torsional vibration with different frequencies is compared. From the conservative estimation results, the torsional damper built in a lock-up clutch of a torque converter is identified to be a vibration isolator. The evaluation results show that the fluid damping by torque converter outperforms the vibration isolation function of a torsional damper, and the isolation performance needs to be enhanced.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.4
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• pp.89-95
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• 2005

This paper intends to identify experimentally the relationship between transverse vibration behavior of a spinning disk and high-frequency fluctuation in the driving torque. A testrig has been developed using a CD-ROM disk, a driving motor with torque-varying capability and a power transmission belt and a laser vibrometer was employed to measure the transverse vibration displacements of the disk for a certain range of the spinning speed. The results show that the spinning speed and the magnitude and frequency of the torque fluctuation affect the stability of the disk. In other word, the torque fluctuation causes the instability of the disk at several ranges of the spinning speed below the critical speed and its effects become larger as the disk spins faster or the magnitude of torque fluctuation becomes bigger. The experimental results are found to be in good agreement with analytical estimation.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.6
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• pp.650-657
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• 2013

This study uses a muscle activation sensor and elbow joint model to develop an estimation algorithm for human elbow joint torque for use in a human-robot interface. A modular-type MVS (Muscle Volume Sensor) and calibration algorithm are developed to measure the muscle activation signal, which is represented through the normalization of the calibrated signal of the MVS. A Hill-type model is applied to the muscle activation signal and the kinematic model of the muscle can be used to estimate the joint torques. Experiments were performed to evaluate the performance of the proposed algorithm by isotonic contraction motion using the KIN-COM$^{(R)}$ equipment at 5, 10, and 15Nm. The algorithm and its feasibility for use as a human-robot interface are verified by comparing the joint load condition and the torque estimated by the algorithm.