• Journal of Power Electronics
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• 제18권6호
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• pp.1720-1728
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• 2018

This paper proposes a novel soft starting algorithm by using PWM inverter technique to control an amplitude of the motor starting current at a single-phase induction motor (SPIM). Traditional SPIM starting methods such as a Split-Phase, Capacitor-Start, Permanent-Split Capacitor (PSC), Capacitor-Start Capacitor-Run (CSCR), basically cannot control the magnitude of starting current due to the fixed system structures. Therefore, in this paper, a soft starting algorithm based on a proportional resonant (PR) control with a variable and constant frequency is proposed to reduce the inrush current and starting up time. In addition, a transition algorithm for operation modes is devised to generate a constant voltage and constant frequency (CVCF). The validity and effectiveness of the proposed soft starting method and transition algorithm are verified through experimental results.

• Journal of Electrical Engineering and Technology
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• 제13권3호
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• pp.1202-1211
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• 2018

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent's chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.891-895
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• 2004

This paper suggests the techniques in determining the values of the steady-state equivalent circuit parameters of a three-phase squirrel-cage induction machine using immune algorithm. The parameter estimation procedure is based on the steady state phase current versus slip and input power versus slip characteristics. The proposed estimation algorithm is of a nonlinear kind based on clonal selection in immune algorithm. The machine parameters are obtained as the solution of a minimization of least-squares cost function by immune algorithm. Simulation shows better results than the conventional approaches.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.330-333
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• 2003

Initial cluster size for clustering of partitioning methods is very important to the clustering result. In K-means algorithm, the result of cluster analysis becomes different with optimal cluster size K. Usually, the initial cluster size is determined by prior and subjective information. Sometimes this may not be optimal. Now, more objective method is needed to solve this problem. In our research, we propose a hybrid genetic algorithm, a tree induction based evolution algorithm, for determination of optimal cluster size. Initial population of this algorithm is determined by the number of terminal nodes of tree induction. From the initial population based on decision tree, our optimal cluster size is generated. The fitness function of ours is defined an inverse of dissimilarity measure. And the bagging approach is used for saying computational time cost.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.21-25
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• 2004

This paper suggests the techniques in determining the values of the steady-state equivalent circuit parameters of a three-phase squirrel-cage induction machine using immune algorithm. The parameter estimation procedure is based on the steady state phase current versus slip and input power versus slip characteristics. The proposed estimation algorithm is of a nonlinear kind based on clonal selection in immune algorithm. The machine parameters are obtained as the solution of a minimization of least-squares cost function by immune algorithm. Simulation shows better results than the conventional approaches.

• 경영과학
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• 제23권1호
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• pp.63-74
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• 2006

Decision tree induction algorithm is one of the most widely used methods in classification problems. However, they could be trapped into a local minimum and have no reasonable means to escape from it if tree algorithm uses top-down search algorithm. Further, if irrelevant or redundant features are included in the data set, tree algorithms produces trees that are less accurate than those from the data set with only relevant features. We propose a hybrid algorithm to generate decision tree that uses genetic programming with sequentially selected features. Correlation-based Feature Selection (CFS) method is adopted to find relevant features which are fed to genetic programming sequentially to find optimal trees at each iteration. The new proposed algorithm produce simpler and more understandable decision trees as compared with other decision trees and it is also effective in producing similar or better trees with relatively smaller set of features in the view of cross-validation accuracy.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제49권10호
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• pp.693-700
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• 2000

A direct torque control algorithm for 3-level inverter-fed induction motors is presented. Conventional voltage selection methods provoke some problems such as stator flux drooping phenomenon and undersirable torque control appeared especially at the low speed operation. To overcome these problems, a proposed method uses intermediate voltage vectors, which are inherently generated in 3-level inverters. In the proposed algorithm, both subdivision of the basic switching sectors and applications of tntermediated voltages improve the low speed operation characteristics. This algorithm basically considers applications in which direct torque controlled induction motors are fed by 3-level inverters with low switching frequency around 500Hz. An adaptive observer is also employed to bring better responses at the low speed operation, by estimating some state-variables, motor speed and motor parameters which take a deep effect on the performance of the low speed operation. Simulation and experiment results verify effectiveness of the proposed algorithm.

• 전기학회논문지P
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• 제65권4호
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• pp.273-279
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• 2016

In this paper, a high-performance control of the induction motor for electric car was implemented to escape dependence of the rare earth magnet. Proposed high-efficiency control algorithm is a Direct Rotor Field-Oriented Control method that is insensitive to the fluctuation of motor parameters. In the DRFOC method, we need to compensate fluctuation of stator transient inductance and magnetizing inductance caused by the magnetic saturation of induction motor in high-speed area. This paper proposes Back-EMF Observer based on stator current estimator of Luenberger style. Motor control system applied the Voltage Feedback Flux Weakening Control method for high-speed operation. The proposed algorithm was verified through tests by the power train of Extended Range Electric Vehicle consists of induction motor and differential gear.

• 전력전자학회논문지
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• 제23권3호
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• pp.199-207
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• 2018

In this paper, an all-metal domestic induction heating (IH) system that can quickly identify ferromagnetic and non-ferromagnetic pots considering temperature changes in the working coil is designed. Load modeling is performed after analyzing the parameters of the pot material and the central misalignment of the working coil. To improve the performance and stability of the all-metal IH cooking heater, a power curve-fitting model is used to design a control system that quickly responds to load parameter fluctuations. In addition, a power control algorithm is established to compensate for the reference value by reflecting the increase in working coil temperature during heating of the non-ferromagnetic pot. The validity of the proposed control algorithm for the all-metal IH is verified by experiments using a 3.2 kW all-metal IH cooking heater.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 A
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• pp.150-152
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• 1994

In this paper, the optimum shape design of stator slot of induction motors for iron loss reduction is proposed. To obtain the flux distribution in induction motors, 2-D finite element method with voltage source is employed. The iron loss is calculated from the iron loss data given by the iron manufacturer. To calculate the sensitivity of iron loss to shape variation, the sensitivity analysis of discrete approach is used. The proposed algorithm is applied to a 3-phase squirrel cage induction motor. The nodes at stator slot boundary of the induction motor are defined as design parameters. By controlling these parameters under the constant volume of iron, we can minimize the iron loss. Furthermore, the stator copper loss is reduced by increasing the slot area. So the stator slot area is determined at the point that the summation of iron loss and copper loss of stator is minimized. Since the constraint of constant volume of iron is nonlinear to the design parameters, the Gradient Projection method is used as an optimization algorithm.