• Wind and Structures
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• v.15 no.5
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• pp.369-383
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• 2012

Researchers have recently begun using high spatial resolution remote-sensing data, which are automatically captured and georeferenced, to assess damage following natural and man-made disasters, in addition to, or instead of employing the older methods of walking house-to-house for surveys, or photographing individual buildings from an airplane. This research establishes quantitative relationships between the damage states observed at ground-level, and those observed from space using high spatial resolution remote-sensing data, for windstorms, for individual site-built one- or two-family residences (FR12). "Degrees of Damage" (DOD) from the Enhanced Fujita (EF) Scale were determined for ground-based damage states; damage states were also assigned for remote-sensing imagery, using a modified version of Womble's Remote-Sensing (RS) Damage Scale. The preliminary developed model can be used to predict the ground-level damage state using remote-sensing imagery, which could significantly lessen the time and expense required to assess the damage following a windstorm.

• Journal of ILASS-Korea
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• v.17 no.1
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• pp.20-26
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• 2012

Inkjet printing is one of the direct writing technologies and is able to form a pattern onto substrate by dispensing droplets in desired position. Also, by inkjet technology manufacturing time and production costs can be reduced, and procedures can be more efficient. To form a metal pattern, it must be harmonized with conductive nano ink, printing process, sintering, and surface treatment. In this study, micro patterning of conductive line has been investigated using the piezoelectric printhead driven by a bipolar voltage signal is used to dispense $20-40{\mu}m$ diameter droplets and silver nano ink which consists of 50 nm silver particles. In addition, hydrophobic treatment of surface, overlap printing techniques, and sintering conditions with changing temperature and times to achieve higher conductivity.

• 한국전기화학회:학술대회논문집
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• 2000.12a
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• pp.51-62
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• 2000

Large plastic Li-ion (PLI) cells (25 to 28-Ah) were fabricated for an EV application. The 28-Ah cells showed high specific energy (160 Wh/kg), high specific power (526 W/g), excellent round-trip energy efficiency $(92\%)$, and low self-discharge rate ($6\%$ in 30 days). A 25-Ah cell of an earlier design showed good cycle life of up to 750 cycles at $100\%$ DOD to $80\%$ of its initial capacity, while cycle life test of a 28-Ah cell of a later design is in progress. Preliminary safety tests were also carried out using 6-Ah cells of a similar electrode design giving very encouraging results for development of a safe hish-energy density PLI battery for EV application.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.538-539
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• 2014

The development of smart grid technologies will enable enhanced utilization of electric vehicles(EV) as portable energy storage devices which can provide power system-wide. Because significant increase of EV in the near future, V2G(Vehicle-to-Grid) system will soon become a reality. This paper presents the optimal method of a battery lifetime depending on depth of discharge(DOD) considering load leveling.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.7
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• pp.950-956
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• 2012

As development of battery technologies, the installation of Battery Energy Storage System (BESS) increased. The BESS can be used for various purposes such like frequency response, load leveling, and fluctuation mitigation of renewable energy generators. In this paper, three state BESS model is proposed. the BESS model considering charge, discharge and keeping efficiency, and life cycle according to depth of discharge (DOD). Then, the benefit and cost of BESS installed at substation for load leveling are summarized. The economic evaluation of BESS is analyzed using net present values (NPV) analysis. In case study, the NPV analysis of NaS battery system is carried out using the proposed BESS model. Because the result of economic evaluation of BESS using nowadays cost data is not positive, the sensitivity analysis of BESS is conducted by changing the capital cost and energy cost.

• Journal of the Korean Applied Science and Technology
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• v.33 no.1
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• pp.83-91
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• 2016

We studied the effect of battery deep cycle according to the way of active materials formation and the creation condition of electrode material, 3BS ($3PbO{\cdot}PbSO_4{\cdot}H_2O$) and 4BS ($4PbO{\cdot}PbSO_4$), in order to develop the batteries for Idle Stop & Go system. During the curing with active materials of anode and cathode, we found that the final creased active material was deformed by temperature control and it effects the durability of batteries. AGM battery and Flooded battery with 3BS active materials have excellent initial performance. And AGM battery with 4BS active materials shows the lower performance relatively. To compare and analyze of the formation efficiency of active materials, we tested the formation chagging steps with 3 steps and 9 steps differently. The results are that AGM battery with 4BS active materials is better on initial performance than AGM battery with 3BS. After the comparison of durability by DOD 17.5% life test, AGM battery is more suitable than flooded battery for the ISG system which needs the frequent deep cycle. In conclusion, AGM battery is the most suitable for ISG system and the life performance shows 80% difference according to the way of formation and curing of AGM batteries.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.7
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• pp.710-721
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• 2013

The noise prediction of motor driving system is one of the most important parts in EV/HEV, as the number of power electronic devices increases. This paper describes the mechanism of noise making process and proposes a simulation model of motor driving system for the prediction of the conducted noise. Theoretical calculations and model based simulations were carried out. DOD-dependent-battery parameters were extracted by AC analysis, and an inverter model including dynamic diode was used. Furthermore, 2-D EM tool was used for the motor modeling and was combined with the circuit models of battery and inverter. The simulated voltages, currents and spectrums in the motor driving system showed qualitatively meaningful results, suggesting the validness of the suggested modeling methods.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.385-391
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• 2023

As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.

• Journal of the Korean Society of Safety
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• v.28 no.6
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• pp.64-72
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• 2013

Construction machinery has been utilized to carry out construction works effectively. Using construction machinery enables a builder to reduce the time and the cost needed for the construction, but the fatal accident caused by it has been increased. This study is intended to identify risk magnitude of accident by kind of construction machinery through interviews with experts. Construction machineries surveyed in this research are excavator, tower crane, lift, mobile crane and forklift, those are the machinery which accident occurs more often than the other machinery. To evaluate the risk of the accidents identified, risk category was determined according to the US DOD system safety program (MIL-STD-882B) considering the risk degree and intensity. As a result, accident occurred in the process of material transport & handling was found to be the most dangerous. On the other hand, the accidents caused by the defective machinery and the poor safety gear were considered to be less dangerous relatively. The risk category by type of construction machinery suggested in this study is expected to provide the basic data in developing the safety guidance for construction project.

• Bulletin of the Korean Chemical Society
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• v.23 no.1
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• pp.75-80
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• 2002

Cycle life tests have been carried out to evaluate the influence of safety valve pressure on valve regulated lead/acid batteries under deep cycling applications. Batteries were cycled at 5 hour rates at 100% DOD, and safety valve pressure was set to 1.08 and 2.00 bar, respectively. The batteries lost 248.3 g and 235.3 g of water for each case after about 1,200 cycles, but the cyclic performances of the batteries were comparable. Most of the gas of the battery during discharging was hydrogen, and the oxygen concentration increased to 18% after 3 hours of charging. The micro structure of the positive active materials was completely changed and the corrosion layer of the positive grid was less than $50{\mu}m$, regardless of the pressure of the safety valve after cycle life tests. The cause of discharge capacity decrease was found to be water loss and the shedding of the positive active materials. The pressure of safety valve does not give little effect to the cyclic performances and the failure modes of the gelled electrolyte valve-regulated lead acid batteries.