• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.20-22
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• 2005

In this paper, we propose fuzzy-neural network controller that combines a fuzzy control and the Neural Networks for high performance control of induction motor drive, Also, this paper is proposed control of maximum torque per ampere of induction motor. This strategy is proposed which is simple in structure and has the honest goal of minimizing the stator current magnitude for given load torque. The performance of the proposed induction motor drive with maximum torque control using fuzzy-neural network controller is verified by simulation at dynamic operation conditions.

• Journal of Magnetics
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• v.18 no.3
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• pp.268-275
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• 2013

This paper shows the characteristics of performance for interior permanent magnet machine (IPM) considering driving conditions such as maximum torque per ampere (MTPA) and flux-weakening control especially in terms of harmonic loss. In particular, based on finite element analysis (FEA), permanent magnet (PM) eddycurrent loss and the harmonic iron loss have been computed where the models have been intentionally designed to identify the effects of pole-slot combinations on the loss while maintaining the required power for electric vehicle. From the analysis results, it was shown that the rotor iron loss and PM eddy-current loss of machine employing fractional slot winding are extremely large at load condition. Furthermore, it was revealed that the harmonic iron loss at high-speed operation is mainly distributed over stator teeth and rotor surface, which may aggravate cooling system of the rotor structure in the vehicle.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.10a
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• pp.363-366
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• 2009

The maximum output torque developed by the machine is dependent on the allowable current rating and maximum voltage that the inverter can supply to the machine. Therefore, to use the inverter capacity fully, it is desirable to use the control scheme considering the voltage and current limit condition, which can yield the maximum torque per ampere over the entire speed range. This controller is controlled speed and current using hybrid PI(HBPI) controller and estimation of speed using ANN. Also, this paper is proposed control of maximum torque per ampere(MTPA) of induction motor. This strategy is proposed which is simple in structure and has the honest goal of minimizing the stator current magnitude for given load torque. The performance of the proposed induction motor drive with maximum torque control using HBPI controller is verified by analysis results at dynamic operation conditions.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.587-588
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• 2010

The maximum output torque developed by the machine is dependent on the allowable current rating and maximum voltage that the inverter can supply to the machine. Therefore, to use the inverter capacity fully, it is desirable to use the control scheme considering the voltage and current limit condition, which can yield the maximum torque per ampere over the entire speed range. This controller is controlled speed using artificial intelligent PI(AIPI) controller. Also, this paper is proposed control of maximum torque per ampere(MTPA) of induction motor. The performance of the proposed induction motor drive with maximum torque control using AIPI controller is verified by analysis results at dynamic operation conditions.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1223-1230
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• 2017

The back emf harmonics of a permanent magnet (PM) synchronous motor is a major source of torque ripple. For torque control applications including column fitted MDPS (motor driven power steering) systems, it is essential to reduce the mechanical vibrations due to torque ripples at low speeds. In this paper, a torque ripple reduction algorithm for interior PM synchronous motors is proposed. The harmonic currents that cancel the $6^{th}$ order torque harmonic are added to the nominal dq currents for MTPA (maximum torque per ampere) operation. The compensated harmonic currents are derived from flux linkage harmonics based on a FFT analysis of the back emf harmonics. Simulation and experimental results verify that the $6^{th}$ order torque harmonic and THD of the torque ripple are reduced by compensating the dq harmonic currents.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.5
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• pp.16-28
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• 2010

This paper proposes maximum torque control of SynRM drive using artificial intelligent(AI)PI 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 axis current for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled AIPI and ANN controller and the operating characteristics controlled by maximum torque control are examined in detail.

• Journal of Magnetics
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• v.16 no.1
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• pp.71-73
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• 2011

Hybrid electric vehicles have attracted much attention of late, emphasizing the necessity of developing traction motors with a high input current and a wide speed range. Among such traction motors, various researches have been conducted on interior permanent-magnet synchronous motors (IPMSMs) with high power density and mechanical solidity. Due to the complexity of its parameters, however, with nonlinear motor characteristics and current vector control, it is actually difficult to accurately estimate the base speed within an actual operating speed range or a voltage limit. Moreover, it is impossible to construct an efficiency map as the efficiency differs according to the control mode. In this study, a simulation method for operation performance considering the nonlinearity of IPMSM was proposed. For this, datasets of various nonlinear parameters were made via the finite-element method and interpolation. Maximum torque-per-ampere and flux-weakening control were accurately simulated using the datasets, and an IPMSM efficiency map was accurately constructed based on the simulation. Lastly, the validity of the simulation was verified through tests.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.8
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• pp.33-39
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• 2005

The maximum output torque and power developed by the machine is ultimately depended on the allowable inverter current rating and maximum voltage which the inverter can supply to the machine. Therefore, considering the limited voltage and current capacities, it is desirable to consider a control method which yields the best possible torque per ampere. In this paper, we propose fuzzy neural network(FNN) controller that combines a fuzzy control and the neural network for high performance control of induction motor drive. This controller composes antecedence of the fuzzy rules and consequence by a clustering method and a multi-layer neural networks. This controller is compounding of advantages that robust control of a fuzzy control and high-adaptive control of the neural networks. Also, this paper is proposed control of maximum torque per ampere(MTPA) of induction moor. This strategy is reposed which is simple in structure and has the honest goal of minimizing the stator current magnitude for given load torque. The performance of the proposed induction motor drive with maximum torque control using FNN controller is verified by analysis results at dynamic operation conditions.