• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.4
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• pp.69-76
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• 2015

This paper presents the results of an investigation into the frequency-dependent electrical parameters for different types of soil as a function of moisture content. The frequency dependence of soil electrical parameters is very important in the design of grounding systems. In fact, the performance of grounding systems is greatly dependent upon various factors such as soil type, particle size, water content, temperature, frequency, and the like. The resistivity and relative permittivity for four different soils were measured and analyzed in the frequency range of 1kHz - 1MHz. Soil resistivity declined as moisture content and frequency increased. In particular, the frequency dependence of soil resistivity was significant as the moisture content was low. In contrast, the relative permittivity of soil dramatically declined at the frequency of 10kHz or below as the moisture content increased, showing the opposite pattern in terms of variation patterns, compared to resistivity.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1998.11a
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• pp.156-161
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• 1998

The purpose of this paper is to determine circuit parameters in the inverter part of the electronic dimming ballast for fluorescent lamps, that is adequate to use with the prevailing dimming controller IC. Firstly, the operating frequency characteristics are investigated by varying circuit parameters of electronic ballasts and are matched with the output characteristics of dimming ballast controller. Secondly, circuit parameter values are determined by using PSpice simulation and operating frequency characteristics. Finally its validity is verified from the electrical and light output characteristics on the prototype of the electronic dimming ballast.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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• pp.16-24
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• 2019

The performance of the battery management system (BMS) algorithm is important for ensuring the stability and efficient operation of battery packs. Such a performance is determined by the internal parameters of the electrical equivalent circuit model (EECM). This study proposes a performance improvement and verification of battery parameters for the BMS algorithm using electrical experiments and tools. The parameters were extracted through electrical characteristic experiments, and an EECM based on Ah counting was designed. Simulation results using the EECM were compared with actual experimental data to determine the best parameter extraction method.

• Transactions on Electrical and Electronic Materials
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• v.17 no.6
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• pp.329-334
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• 2016

In this work, the temperature dependence of electrical parameters of nanoscale SOI (silicon-on-insulator) TG (triple gate) n-FinFET (n-channel Fin field effect transistor) was investigated. Numerical device simulator $ATLAS^{TM}$ was used to construct, examine, and simulate the structure in three dimensions with different models. The drain current, transconductance, threshold voltage, subthreshold swing, leakage current, drain induced barrier lowering, and on/off current ratio were studied in various biasing configurations. The temperature dependence of the main electrical parameters of a SOI TG n-FinFET was analyzed and discussed. Increased temperature led to degraded performance of some basic parameters such as subthreshold swing, transconductance, on-current, and leakage current. These results might be useful for further development of devises to strongly down-scale the manufacturing process.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.101-107
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• 2008

We introduce an optimization of fuzzy set-fuzzy systems based on IG (Information Granules). The proposed fuzzy model implements system structure and parameter identification by means of IG and GAs. The concept of information granulation was coped with to enhance the abilities of structural optimization of the fuzzy model. Granulation of information realized with C-Means clustering helps determine the initial parameters of the fuzzy model such as the initial apexes of the membership functions in the premise part and the initial values of polynomial functions in the consequence part of the fuzzy rules. The initial parameters are adjusted effectively with the help of the GAs and the standard least square method. To optimally identify the structure and the parameters of the fuzzy model we exploit GAs with successive tuning method to simultaneously search the structure and the parameters within one individual. We also consider the variant generation-based evolution to adjust the rate of identification of the structure and the parameters in successive tuning method. The proposed model is evaluated with the performance of the conventional fuzzy model.

• Journal of Power Electronics
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• v.18 no.1
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• pp.92-102
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• 2018

A sliding mode control (SMC) for servo motors based on the differential evolution (DE) algorithm, called DE-SMC, is proposed in this study. The parameters of SMC should be designed exactly to improve the robustness, realize the precision positioning, and reduce the steady-state speed error of the servo drive. The main parameters of SMC are optimized using the DE algorithm according to the speed feedback information of the servo motor. The most significant influence factor of the DE algorithm is optimization iteration. A suitable iteration can be achieved by the tested optimization process profile of the main parameters of SMC. Once the parameters of SMC are optimized under a convergent iteration, the system realizes the given performance indices within the shortest time. The experiment indicates that the robustness of the system is improved, and the dynamic and steady performance achieves the given performance indices under a convergent iteration when motor parameters mismatch and load disturbance is added. Moreover, the suitable iteration effectively mitigates the low-speed crawling phenomenon in the system. The correctness and effectiveness of DE-SMC are verified through the experiment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.128-133
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• 2010

This paper presents a method for estimating the parameters of dynamic models for induction motor dominating loads. Using particle swarm optimization, the method finds the adequate set of parameters that best fit the sampling data from the measurement for a period of time, minimizing the error of the outputs, active and reactive power demands and satisfying the steady-state error criterion.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.852-856
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• 2004

An induction motor is one of the most popular electrical apparatuses owing to its simple structure and robust construction. Parameter identification of the induction motor has long been researched either for a vector control technique or fault detection. Since vector control is a well-established technique for induction motor control, this paper concentrates on successive identification of physical parameters with on-load data for the purpose of condition monitoring and/or fault detection. For extracting six physical parameters from the on-load data in the framework of the induction motor state equation, unmeasured initial state values and profiles of load torque have to be estimated as well. However, the analytic optimization methods in general fail to estimate these auxiliary but significant parameters owing to the difficulty of obtaining their gradient information. In this paper, the univariate dynamic encoding algorithm for searches (uDEAS) newly developed is applied to the identification of whole unknown parameters in the mathematical equations of an induction motor with normal operating data. Profiles of identified parameters appear to be reasonable and therefore the proposed approach is available for fault diagnosis of induction motors by monitoring physical parameters.

• Journal of Electrochemical Science and Technology
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• v.6 no.4
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• pp.131-138
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• 2015

Electrical discharge machining is an unconventional machining process in which successive sparks applied to machine the electrically conductive materials. Any changes in electrical discharge machining parameters lead to the pieces with distinct surface roughness. The electrical discharge machining process is well applied for high hardness materials or when it is difficult to use traditional techniques to do material removing. Furthermore, this method is widely applied in industries such as aerospace, automobile, molding, and tool making. CK45 is one of the important steels in industrial and electrical discharge machining can be considered as a proper way for its machining because of high hardness of CK45 after thermal operation of the electrical discharge machining process. Optimization of surface roughness as an output parameters as well as electrical discharge machining parameters including current, voltage and frequency for electrical discharge machining of CK45 has been studied using copper tools and kerosene as the dielectric. For such a purpose and to achieve the precise statistical analysis of the experiment results design of experiment was applied while non linear regression method was chosen to assess the response of surface roughness. Then, the results were analyzed by means of ANOVA method and machining parameters with more effects on the desired outputs were determined. Finally, mathematical model obtained for surface roughness.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.635-637
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• 1996

Track circuit decides whether the section is occupied by train or free using the electrical characteristics of the rail, and sends information to the train using the rail as the medium of communication. So the electrical parameters of the rail are important to the track circuits. But they are influenced by the frequency of the transmitted signal and the environments like rain, snow and location of the rail. In this paper, the parameters of the rail is practically measured using the measurement method based on the 2-port network. The measurement demonstrates that the parameters of the rail is dependent on the frequency of the signal flowing on the rail and the environments like wheather. So this analysis of the parameters helps the design of track circuits.