• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.3
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• pp.176-182
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• 2021

This research proposes a high-frequency circuit that can accurately predict the differential mode noise of single-phase inverters at the circuit design stage. Proposed single-phase inverter high frequency circuit in the work is a form in which harmonic impedance components are added to the basic single-phase inverter circuit configuration. For accurate noise prediction, parasitic components present in each part of the differential noise path were extracted. Impedance was extracted using a network analyzer and Q3D in the measurement range of 150 kHz to 30 MHz. A high-frequency circuit model was completed by applying the measured values. Simulations and experiments were conducted to confirm the validity of the high-frequency circuit. As a result, we were able to predict the resonance point of the differential mode voltage extracted as an experimental value with a high-frequency circuit model within an approximately 10% error. Through this outcome, we could verify that differential mode noise can be accurately predicted using the proposed model of the high-frequency circuit without a separate test bench for noise measurement.

• Journal of Hydrogen and New Energy
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• v.35 no.2
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• pp.121-128
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• 2024

In this study, a dynamic simulation model of a heavy-duty truck, equipped with a fuel cell power-train, has been developed and the dynamic behavior of the fuel cell stack has bee investigated using. Output change simulations were performed according to several drive cycle load change of a fuel cell truck. Mathworks' Simulink and Simscape program were used to develop the model. The model is comprised of fuel cell power train, power converter system and truck vehicle part. The vehicle runs at targeted speed of the truck, which is set as the load of the system. The dynamic behavior of the fuel cell stack according to the weight difference were analyzed, and based on this, the dynamic characteristics of the fuel cell output power and battery state with simple load was analyzed.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.257-280
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• 2022

In this study, we analyzed comments on news articles of representative companies of the three industries (i.e., semiconductor, secondary battery, and bio industries) that had been listed as national strategic technology projects of South Korea to identify public opinions towards them. In addition, we analyzed the relationship between changes in public opinion and stock price. 'Samsung Electronics' and 'SK Hynix' in the semiconductor industry, 'Samsung SDI' and 'LG Chem' in the secondary battery industry, and 'Samsung Biologics' and 'Celltrion' in the bio-industry were selected as the representative companies and 47,452 comments of news articles about the companies that had been published from January 1, 2020, to December 31, 2020, were collected from Naver News. The comments were grouped into positive, neutral, and negative emotions, and the dynamic topics of comments over time in each group were analyzed to identify the trends of public opinion in each industry. As a result, in the case of the semiconductor industry, investment, COVID-19 related issues, trust in large companies such as Samsung Electronics, and mention of the damage caused by changes in government policy were the topics. In the case of secondary battery industries, references to investment, battery, and corporate issues were the topics. In the case of bio-industries, references to investment, COVID-19 related issues, and corporate issues were the topics. Next, to understand whether the sentiment of the comments is related to the actual stock price, for each company, the changes in the stock price and the sentiment values of the comments were compared and analyzed using visual analytics. As a result, we found a clear relationship between the changes in the sentiment value of public opinion and the stock price through the similar patterns shown in the change graphs. This study analyzed comments on news articles that are highly related to stock price, identified changes in public opinion trends in the COVID-19 era, and provided objective feedback to government agencies' policymaking.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.1
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• pp.55-64
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• 2015

Wind turbine market is showed height growth rate of about 30% for year, and is increasingly growing. Total rate of domestic wind turbine installation is showing share of 0.2% of the global market that is 380MW. However, wind turbine installed in domestic are foreign product more than 90%. Similarly, Datalogger of pretest system for ocean wind turbine plant installation has been leaked huge cost to abroad by mostly abroad company product. In this paper, we proposed pretest weather resource measurement system for efficiency and investment cost cutting of wind turbine construction work. Preset weather resource measurement system is ocean weather resource measurement datalogger based on wireless communication(wifi) that have consist of hardware and software(wind rose) that is able to monitoring as datalogger of wireless bridge and battery state, wind direction, wind speed, temperature, humidity, radiation around weather tower and is able to analysis of measured data.

• Journal of Energy Engineering
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• v.29 no.3
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• pp.74-85
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• 2020

This paper presents an algorithm that evaluated the overload influence by bus upon the distribution system by calculating the daily load curve of PEVs charging by bus based on the daily charging patterns of PEVs according to PEVs penetration scenarios. The proposed algorithm calculates the number of PEVs to estimate the number of households by bus; the probability density function of the charging start time of PEVs, considering driving characteristics of PEVs and the daily load curve of PEVs charging by bus considering battery characteristics according to PEVs penetration scenarios. To verify the evaluation of the overload influence by bus on the distribution system in terms of the proposed algorithm, the cases were reviewed on the target bus(apartment and detached houses) among the feeders of the distribution systems at Dongtan new-town in Korea.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.11
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• pp.997-1004
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• 2011

A fault detection algorithm of a charge and discharge system to ensure the safe use of hybrid electric vehicle is proposed in this paper. This algorithm can be used as a complementary way to existing fault detection technique for a charge and discharge system. The proposed algorithm uses a SVDD technique, which additionally utilizes two methods for learning a large amount of data; one is to incrementally learn a large amount of data, the other one is to remove the data that does not affect the next learning using a new data reduction technique. Removal of data is selected by using lines connecting support vectors. In the proposed method, the data processing speed is drastically improved and the storage space used is remarkably reduced than the conventional methods using the SVDD technique only. A battery data and speed data of a commercial hybrid electrical vehicle are utilized in this study. A fault boundary is produced via SVDD techniques using the input and output in normal operation of the system without using mathematical modeling. A fault detection simulation is performed using both an artificial fault data and the obtained fault boundary via SVDD techniques. In the fault detection simulation, fault detection time via proposed algorithm is compared with that of the peak-peak method. Also the proposed algorithm is revealed to detect fault in the region where conventional peak-peak method is never able to do.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.14-22
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• 2007

Wireless sensor networks are composed of numerous sensor nodes and exchange or recharging of the battery is impossible after deployment. Thus, sonsor nodes must be very energy-efficient. As neighboring sensor nodes generally have the data of similar information, duplicate transmission of similar information is usual. To prevent energy wastes by duplicate transmissions, it is advantageous to organize sensors into clusters. The performance of clustering scheme is influenced by the cluster-head election method and the size or the number of clusters. Thus, we should optimize these factors to maximize the energy efficiency of the clustering scheme. In this paper, we propose a new energy consumption model for LEACH which is a well-known clustering protocol and determine the optimal number of clusters based on our model. Our model has accuracy over 80% compared with the simulation and is considerably superior to the existing model of LEACH.

• Journal of the Microelectronics and Packaging Society
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• v.12 no.3 s.36
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• pp.267-274
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• 2005

This paper presents the fabrication of surface acoustic wave (SAW)-based pressure sensor for long-term stable mechanical compression force measurement. SAW pressure sensor has many attractive features for practical pressure measurement: no battery requirement, wireless pressure detection especially at hazardous environments, and easy other functionality integrations such as temperature, humidity, and RFID. A $41^{\circ}$ YX $LiNbO_3$ piezoelectric substrate was used because of its high SAW propagation velocity and large values of electromechanical coupling factors $K^2$. A silicon substrate with $\~200{\mu}m$ deep cavity was bonded to the diaphragm with epoxy, in which gold was covered all over the inner cavity in order to confine electromagnetic energy inside the sensor, and provide good isolation of the device from its environment. The reflection coefficient $S_{11}$ was measured using network analyzer. High S/N ratio, sharp reflected peaks, and clear separation between the peaks were observed. As a mechanical compression force was applied to the diaphragm from top with extremely sharp object, the diaphragm was bended, resulting in the phase shifts of the reflected peaks. The phase shifts were modulated depending on the amount of applied mechanical compression force. The measured $S_{11}$ results showed a good agreement with simulated results obtained from equivalent admittance circuit modeling.

• Journal of the Korean Electrochemical Society
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• v.16 no.3
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• pp.177-183
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• 2013

As the development of available binder in the harsh conditions is needed, we propose the proper binder for high-voltage lithium-ion secondary batteries based on the quantum chemistry modeling. The optimized structures, HOMO (Highest Occupied Molecular Orbital) energies and ionization potentials of 4 binders, which were considered from monomer to tetramer, were investigated by the semi-empirical and DFT (Density Functional Theory) calculations. The results show that the ionization potential values by calculation tend to be close to the oxidation potentials from the measurement of linear sweep voltametry (LSV). The order of oxidative resistance from high value to low value is following: poly(hexafluropropylene), poly(vinylidene fluoride), poly(methyl acrylate) and poly(acryl amide). Also these results correspond with the experimental values. Thus, we find the reason why HOMO (Highest Occupied Molecular Orbital) energy of PHFP has the highest value than other binders by analysis of HOMO orbital structures.

• KEPCO Journal on Electric Power and Energy
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• v.1 no.1
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• pp.33-38
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• 2015

Energy storage systems (ESSs) have been utilized widely in the world to optimize the power operation system and to improve the power quality. As lithium secondary batteries are the main power supplier for ESSs, it is very important to predict its cycle and power degradation behavior. In particular, the power, one of the hardest electrochemical properties to measure, needs lots of resources such as time and facilities. Due to these difficulties, computer modelling of lithium secondary batteries is applied to predict the DC-IR and power value during charging and discharging as a function of state of charge (SOC) by using pulse-based measurement methods. Moreover, based on the hybrid pulse power characteristics (HPPC) and J-Pulse (JEVS D 713, Japan Electric Vehicle Association Standards) methods, their electrochemical properties are also compared and discussed.