• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.3
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• pp.139-146
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• 2003

In this paper, the steady-state operating performance analysis for the three-phase squirrel cage rotor self-excited induction generator (SEIG) driven by a variable-speed prime mover (VSPM) in addition to a constant-speed prime mover (CSPM) is presented on the basis of an effective algorithm based on its frequency-domain equivalent circuit. The operating characteristics of the three-phase SEIG coupled by a VSPM and/or a CSPM are evaluated on line processing under the condition of the electrical passive load parameters variations with simple and efficient computation processing procedure in unregulated voltage control loop scheme. A three-phase SEIG prototype setup with a VSPM as well as a CSPM is implemented for the small-scale clean renewable and alternative energy utilizations. The experimental operating characteristic results are illustrated and give good agreements with the simulation ones.

• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.79-89
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• 2019

Classification models pertaining to receiver operating characteristic (ROC) curve analysis have been extended from univariate to multivariate setup by linearly combining available multiple markers. One such classification model is the multivariate ROC curve analysis. However, not all markers contribute in a real scenario and may mask the contribution of other markers in classifying the individuals/objects. This paper addresses this issue by developing an algorithm that helps in identifying the important markers that are significant and true contributors. The proposed variable selection framework is supported by real datasets and a simulation study, it is shown to provide insight about the individual marker's significance in providing a classifier rule/linear combination with good extent of classification.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.4
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• pp.6-11
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• 2016

There has been an increase in the number of researches on the segment for commercialization after developing avionics systems. In this paper, we have applied a commercial off-the-shelf(COTS) operating systems in an aircraft mission computer. We used UAV collision avoidance algorithms to compare the performance of COTS operating systems. The UAV collision avoidance algorithms were tested on different operating systems to compare the performances of the operating systems. The measured parameters are memory usage and processing time. We have verified that the UAV collision avoidance algorithms worked successfully and compared the performance of each operating system.

• 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.170-175
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• 2003

A control algorithm is developed for highly efficient operation of auxiliary power unit (APU) that consists of a diesel engine and a directly coupled induction generator in series hybrid electric Bus (SHEB). In a series hybrid configuration the APU supplies the electric power needed for maintaining the state of charge (SOC) of the battery unit in various conditions of vehicle operation. As the rotational speed of generator does not depend on the vehicle speed, an optimized operation of engine-generator unit based on the efficiency map of each component can be achieved. The output torque of diesel engine can be controlled by the amount of fuel injection, and the power converted from mechanical to electrical energy can be adjusted by generate control unit (GCU) using the decoupling vector control of torque and flux. As for the given reference of the generating power, the multiply of speed and torque, many combinations of operating speed and torque are possible. The algorithm decides the new operating point based on the engine efficiency map and generator characteristic curve. During the transition of operating points, the speed controller saturation is avoided using variable limit and filtering of generator torque reference. A test rig and SHEB consist of a 1.5L diesel engine and a 30kw induction generator are constructed by Hyundai Motor Company.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.212-216
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• 1999

We propose a method for simulation optimization using stochastic genetic algorithm(GA) to get the best design and operating policies in a Direct-Input-Output Automated Manufacturing System (DIOMS).

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.3
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• pp.133-140
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• 2006

This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor(SynRM) which minimizes the copper and iron losses. Also, this paper presents a speed estimated control scheme of SynRM using artificial neural network(ANN). There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of ANN is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.7
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• pp.352-357
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• 2005

In competitive electricity markets, the System Operator (SO) coordinates the overall maintenance schedules when the collective maintenance schedule reported to 50 by Gencos not satisfy the specified operating criteria, such as system reliability or supply adequacy. This paper presented a method that divides generator maintenance scheduling of the 50 into a master-problem and a sub-problem. Master-problem is schedule coordination and sub-problem is DC-optimal power flow. If sub-problem is infeasible, we use the algorithm of modifying operating criteria of master-problem. And, the 50 should use the open information only, because the information such as cost function of a generator and bidding Price is highly crucial for the strategies of profit maximization.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.93-101
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• 1989

The classic machine repair problem is extended to the case where a number of different machines are arranged in the sequence of operation. The steady-state availability of the system with a series of operating machines is maximized under some constraints such as total cost, available space. In order to find the optimal numbers of spare units and repair channels for each operating machine, the problem is formulated as non-linear integer programming(NLIP) problem and an efficient algorithm, which is a natural extension of the new Lawler-Bell algorithm of Sasaki et al., is used to solve the NLIP problem. A numerical example is given to illustrate the algorithm.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1287-1295
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• 2002

In this work, the fuel economy of a parallel hybrid electric vehicle is investigated. A vehicle control algorithm which yields operating points where operational cost of HEV is minimal is suggested. The operational cost of HEV is decided considering both the cost of fossil fuel consumed by an engine and the cost of electricity consumed by an electric motor. A procedure for obtaining the operating points of minimal fuel consumption is introduced. Simulations are carried out for 3 variations of HEV and the results are compared to the fuel economy of a conventional vehicle in order to investigate the effect of hybridization. Simulation results show that HEV with the vehicle control algorithm suggested in this work has a fuel economy 45% better than the conventional vehicle if braking energy is recuperated fully by regeneration and idling of the engine is eliminated. The vehicle modification is also investigated to obtain the target fuel economy set in PNGV program.