• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.47-57
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• 2006

The paper is proposed maximum torque control of SynRM drive using adaptive teaming mechanism-fuzzy neural network(ALM-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. The proposed control algorithm is applied to SynRM 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 analysis results to verify the effectiveness of the ALM-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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.8
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• pp.85-93
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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 posed maximum torque control of IPMSM for high speed drive. 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. The proposed control algorithm is applied to IPMSM drive system for high speed drive, the operating characteristics controlled by maximum torque control are examined in detail by experiment.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.5
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• pp.474-482
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• 1999

In this paper, a new field weakening algorithm which maximizes the output torque not only in steady state b but also in transient state is proposed. Considering both voltage and current limit of system, analytic solutions f for optimal torque utilization in field weakening region I and region II are obtained. This algorithm finds optimal currents considering dynamic vol떠ge limit based on flux and speed. So the maximum usage of stator v voltage even in transient state results in the maximum torque and fast response time. Simulation and e experimental results show the effectiveness of the proposed field weakening scheme.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.110-117
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• 2013

Maximum Torque Per Amp (MTPA) control for induction motor drives seeks to achieve a desired torque with the minimum possible stator current. This is favorable in terms of inverter operation and nearly optimal in terms of motor efficiency. However, rotor resistance variation can cause significant performance degradation. This work demonstrates that existing MTPA controls perform sub-optimally as temperature varies. An adaptive MTPA control strategy is proposed that always achieves optimal performance without exhibiting hunting phenomenon regardless of rotor temperature. The proposed control is experimentally shown to accurately achieve the desired torque.

• Journal of Power Electronics
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• v.14 no.2
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• pp.341-350
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• 2014

The torque ripple of switched reluctance motors (SRMs) is the main disadvantage that limits the industrial application of these motors. Although several methods for smooth-toque operation (STO) have been proposed, STO works well only within a certain torque and speed range because of the constraints of the supply voltage and peak current. Based on previous work that sought to expand the STO range, a scheme is developed in this study to determine the maximum smooth torque range at each speed. The relationship between the maximum smooth torque and speed is defined as the smooth torque speed characteristics (STSC), a concept similar to torque speed characteristics (TSC). STSC can be utilized to evaluate torque utilization by comparing it with TSC. Thus, the concept benefits the special design of SRMs, especially for the generation of smooth torque. Furthermore, the torque sharing function (TSF) derived from the proposed method can be applied to STO, which produces a higher smooth torque over a wider speed range in contrast to four typical TSFs. TSimulation and experimental results verify the proposed method.

• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.3
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• pp.221-229
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• 2003

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 for electric vehicle drive. 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. The proposed control algorithm is applied to IPMSM drive system for electric vehicle drive, the operating characteristics controlled by maximum torque control are examined in detail by simulation.