• Proceedings of the KIPE Conference
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• 2004.07b
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• pp.959-962
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• 2004

A strategy for a torque ripple reduction drive of single-phase SRM with high power factor is proposed. The drive for switched reluctance motor (SRM) is presented to achieve sinusoidal, near unity power factor input current with low torque ripple. The proposed SRM drive has no additional active switch. And a single-stage approach, which combines a DC link capacitor used as do source and a drive used for driving the motor into one power stage, has a simple structure and low cost. The characteristics and validity of the proposed circuit is discussed in depth through the experimental results.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.832-835
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• 2003

This paper presents a design and characteristics analysis of a SRM drive for EPS(Electrically Power Steering) application. A conventional driving room space and mechanical structure are suggested in design stage. In the restricted design conditions, motor parameters are determined for sufficient torque and speed. For the smooth torque generation and simple circuit of power system, 12/8 motor drive is considered. With FEM and magnetic circuit analysis, designed motor is simulated to meet the requirement of specifications. Effectiveness of the suggested SRM drive for EPS application is verified by the manufactured prototype motor drive tests.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.101-116
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• 2002

Modern vehicles require a high degree of refinement, including good driveability to meet customer demands. Vehicle driveability, which becomes a key decisive factor for marketability, is affected by many parameters such as engine control and the dynamic characteristics in drive lines. Therefore, Engine and drive train characteristics should be considered to achieve a well balanced vehicle response simultaneously. This paper describes analysis procedures using a mathematical model which has been developed to simulate spark timing control logic. Inertia mass moment, stiffness and damping coefficient of engine and drive train were simulated to analyze the effect of parameters which were related vehicle dynamic behavior. Inertia mass moment of engine and stiffness of drive line were shown key factors for the shuffle characteristics. It was found that torque increase rate, torque reduction rate and torque recovery timing and rate influenced the shuffle characteristics at the tip-in condition for the given system in this study.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.574-577
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• 1996

In order to reduce the torque pulsation caused by non-sinusoidal flux distribution of the brushless direct drive motor(BLDDM), a new torque control technique is proposed. The linkage flux of the BLDDM is first estimated by using the model reference adaptive system (MRAS) technique and the instantaneous torque of the BLDDM is then estimated from the mathematical model including this estimated linkage flux. By using the estimated instantaneous torque of the BLDDM, the minor torque control loop to suppress the undesirable torque pulsation is designed. To show the effectiveness of the proposed control scheme, the simulations and experiments are carried out for the DSP-based BLDDM drive system with a power rate of 120W. It is well demonstrated from these results that the torque and speed control performance of the BLDDM is much improved by employing the proposed control scheme.

• Proceedings of the KIEE Conference
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• summer
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• pp.1022-1024
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• 2004

This paper presents a design and characteristics analysis of an SRM drive for EPS application. A rack mounted EPS system is considered in this paper. In the unrestricted design conditions, motor parameters are determined for sufficient torque and speed with some restrictions. For the smooth torque generation and simple circuit of power system, 12/8 motor drive is considered. With FEM and magnetic circuit analysis, redesigned motor is simulated to meet the requirement of specifications. Effectiveness of the suggested SRM drive for EPS application is verified by redesigned motor drive tests.

• 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 B
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• v.55 no.2
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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.

• 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 B
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• v.55 no.8
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• pp.389-395
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• 2006

In the single-phase switched reluctance motor (SRM) drive, the required DC source is generally supplied by the circuit consisting of bridge rectifier with diodes and many filter capacitances connected with AC source. Although the peak torque ripple of SRM is small because of large capacity of the capacitance, the charge and discharge time swhich the AC source acts on the capacitance are small and the peak current will pass on the side of source, so power factor and system efficiency decrease. Therefore a novel SRM drive system is presented in this paper, which includes drive circuit realizing reduction of torque ripple and improvement of power factor and switching topology. The proposed drive circuit consists of one switching part and diodes which can separate the output of AC/DC rectifier from the large capacitance and supply power to SRM alternately in order to realize reduction of torque ripple and improvement of power factor through the turn on and turn off of switching part. In addition, the validity of method is tested by simulation and experiment.