• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 전력전자학술대회 논문집
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• pp.114-117
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• 2001

In the Electric Vehicle(EV) driving system, the Battery Management System(BMS) is very important and an essential equipment. Particularly, BMS monitors the State of Charge(SOC), voltage, current, and temperature of the battery modules when Electric Vehicle is in the state of motoring or charging. Major roles of BMS are like these the first, estimation of State of Charge(SOC), the second, detection of the unbalance of the voltage between battery modules, the third, control of the available limit of the voltage and temperature of batteries by monitoring the batteries status during motoring or charging. In this research, We have focused on estimating SOC of battery according to the status of Electric Vehicle and the BMS operation algorithm. The result for algorithm of SOC estimation is presented. It have been modified, compensated, and verified by means of the experiment.

• 대한건축학회논문집:구조계
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• 제36권3호
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• pp.169-176
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• 2020

The authors developed a nodal network model that simulates the flow of moist air and the thermal behavior of a target area. The nodal network model was enhanced using a parameter estimation technique based on the measured temperature, humidity, and schedule data. However, the nodal model is not good enough for predicting humidity of the target space, having 55.6% of CVRMSE. It is because re-evaporation effect could not be modeled due to uncertain factors in the field measurement. Hence, a data-driven model was introduced using an artificial neural network (ANN). It was found that the data-driven model is suitable for predicting the condensation compared to the nodal model satisfying ASHRAE Guideline with 3.36% of CVRMSE for temprature, relative humidity, and surface temperature on average. The model will be embedded in automated devices for real-time predictive control, to minimize the risk of surface condensation at dressroom in an apartment housing.

• 대기
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• 제34권2호
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• pp.107-121
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• 2024

In this study, we empirically analyzed the impact of physical risks due to climate change on the soundness and operational performance of the financial industry by combining economics and climatology. Particularly, unlike previous studies, we employed the Seasonal-Trend decomposition using LOESS (STL) method to extract trends of climate-related risk variables and economic-financial variables, conducting a two-stage empirical analysis. In the first stage estimation, we found that the delinquency rate and the Bank for International Settlement (BIS) ratio of commercial banks have significant negative effects on the damage caused by natural disasters, frequency of heavy rainfall, average temperature, and number of typhoons. On the other hand, for insurance companies, the damage from natural disasters, frequency of heavy rainfall, frequency of heavy snowfall, and annual average temperature have significant negative effects on return on assets (ROA) and the risk-based capital ratio (RBC). In the second stage estimation, based on the first stage results, we predicted the soundness and operational performance indicators of commercial banks and insurance companies until 2035. According to the forecast results, the delinquency rate of commercial banks is expected to increase steadily until 2035 under assumption that recent years' trend continues until 2035. It indicates that banks' managerial risk can be seriously worsened from climate change. Also the BIS ratio is expected to decrease which also indicates weakening safety buffer against climate risks over time. Additionally, the ROA of insurance companies is expected to decrease, followed by an increase in the RBC, and then a subsequent decrease.

• Journal of Power Electronics
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• 제13권4호
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• pp.516-527
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• 2013

This paper presents a new overall system for state-of-available-power (SoAP) prediction for a lithium-ion battery pack. The essential part of this method is based on an adaptive network architecture which utilizes both fuzzy model (FIS) and artificial neural network (ANN) into the framework of adaptive neuro-fuzzy inference system (ANFIS). While battery aging proceeds, the system is capable of delivering accurate power prediction not only for room temperature, but also at lower temperatures at which power prediction is most challenging. Due to design property of ANN, the network parameters are adapted on-line to the current battery states (state-of-charge (SoC), state-of-health (SoH), temperature). SoC is required as an input parameter to SoAP module and high accuracy is crucial for a reliable on-line adaptation. Therefore, a reasonable way to determine the battery state variables is proposed applying a combination of several partly different algorithms. Among other SoC boundary estimation methods, robust extended Kalman filter (REKF) for recalibration of amp hour counters was implemented. ANFIS then achieves the SoAP estimation by means of time forward voltage prognosis (TFVP) before a power pulse occurs. The trade-off between computational cost of batch-learning and accuracy during on-line adaptation was optimized resulting in a real-time system with TFVP absolute error less than 1%. The verification was performed on a software-in-the-loop test bench setup using a 53 Ah lithium-ion cell.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 추계학술대회
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• pp.183-185
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• 2015

최근 기계학습기반 빅데이터 분석이 많은 주목을 받으며 축산분야에도 다양한 기계학습 방안들이 적용되고 있다. 많은 양의 생체데이터와 환경데이터에 기계학습기법을 적용하여 분석함으로써 이전에는 발견하지 못했던 새로운 사실들을 밝혀낼 수 있다. 본 연구에서는 실험돈사에서 수집된 데이터를 기반으로 비육돈의 비율일당증체를 예측하는 방안에 대해서 다루었다. 비율일당증체 예측을 위해서 매일 측정된 온도/습도/이산화탄소/풍속의 일평균/일최소/일최대 데이터(환경데이터)과 비율일당증체(생체데이터)를 이용하였고, 트리기반 알고리즘을 사용하여 비율일당증체 예측수식을 도출하였다. 이를 통해 평균 온도가 비율일당증체에 가장 큰 영향을 미치는 요소인 것을 보였다. 본 연구의 결과는 각 양돈농가에서 비육돈의 성장을 예측하는데 유용하게 활용될 수 있을 것이다.

• 농업과학연구
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• 제41권4호
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• pp.481-485
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• 2014

According to statistical data the past ten years, cultivation area and yield of radish are steadily decreasing. This phenomenon cause instability of radish's supply due to meteorological chage, even if radish's yield per unit area is increasing by cultivation technological development. These problems raise radish's price. So, we conducted study on meteorological factors for accuracy improvement of radish yield estimation. Panel analysis was used with two-way effect model considering group effect and time effect. As the result, we show that mixed effects model (fixed effect: group, random effects: time) was statistical significance. According to the model, a rise of one degree in the average air temperature on August will decrease radish's yield per unit area by $428kg{\cdot}10a^{-1}$ and that in the average air temperature on October will increase radish's yield per unit area by $438kg{\cdot}10a^{-1}$. The reason is that radish's growth will be easily influenced by meteorological condition of a high temperature on August and by meteorological condition of a low temperature on Octoboer.

• 대기
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• 제17권3호
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• pp.255-268
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• 2007

This study generated and evaluated the high resolution (5 km) gridded data of monthly mean, maximum and minimum temperature from 2002 to 2005 over South Korea using a modified PRISM(Parameter-elevation Regressions on Independent Slopes Model: K-PRISM) developed by Daly et al. (2003). The performance of K-PRISM was evaluated by qualitative and quantitative ways using the observations and gridded data derived by inverse distance weighting (IDW) and hypsometric methods (HYPS). For the generation of high resolution gridded data, geographic informations over South Korea, such as the digital elevation, topographic facet and coastal proximity, are derived from the 1 km digital elevation data. The spatial patterns of temperature derived by K-PRISM were more closely linked to topography and coastal proximity than those by IDW. The K-PRISM performed much better than IDW for all months and temperatures, but it was equal to or slightly better than the HYPS. And the performances of K-PRISM were better in the minimum and mean temperature (winter) than the in maximum temperature (summer).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.847_848
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• 2009

This paper shows the temperature rise of the high voltage GIS bus bar. The temperature rise in GIS bus bar is due to Joule‘s losses in the conductor and the induced eddy current in the tank. The power losses of a bus bar calculated from the magnetic field analysis are used as the input data for the thermal analysis to predict the temperature. The required analysis is a couple-field Multiphysics that accounts for the interactions between three-dimensional AC harmonic magnetic and fluid fields. The heat transfer calculation using the fluid analysis is done by considering the natural convection and the radiation from the tank to the atmosphere. Consequently, because temperature distributions by couple-field Multiphysics (coupled magnetic-fluid) have good agreement with results of temperature rise test, the proposed couple-field Multiphysics technique is likely to be used in a conduction design of the single-pole and three pole-encapsulated bus bar in GIS..

• 대한기계학회:학술대회논문집
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• 대한기계학회 2002년도 학술대회지
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• pp.403-406
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• 2002

A number of the experiments on the phenomenon in which the thermal energy was transferred from a hot sphere to the surrounding water through the film boiling process had been conducted. As the sphere only carried the thermal energy associated with its initially high temperature but did not contain any other thermal source, the film boiling was only driven by the decreasing temperature of the sphere and, thus, was time dependent. The results from the experiments showed that the temperature of the sphere was slowly decreased in the beginning. This corresponded to the period in which the sphere was penetrating the water surface. Later, when the sphere was fully submerged and the transition film boiling was observed over the whole surface, the temperature of the sphere was decreased relatively much faster. In the last stage, the temperature of the sphere was again slowly decreased. This was considered caused by the relatively low temperature of the sphere, which reduced and later ceased the film boiling process. In addition, the estimation of the departure rate of the steam bubbles from the film layer was also correlated for the experiments.

• Journal of Advanced Marine Engineering and Technology
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• 제9권4호
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• pp.317-327
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• 1985

In the case of temperature control of air conditioning and refrigerating system, it is possible to operate the system continuously by controlling the cooling capacity of refrigerating machines. But on-off control system has been adopted for refrigerating system which has more large capacity than that required to remove the generated heat. In this on-off control system, it can be considered that there exists some optimum condition for the refrigerating capacity, operating cycle, running hour, and the temperature difference between thermostat setting value and real one. In this paper, an equation was derived to express the temperature variation of the refrigerated object (Nybrine) and later two evaluating functions were derived. One is for the temperature difference and another is for operating cycle and running hour. The weighted sum of these two functions is defined as the criterion function for the evaluation of the control performance of the system, and then the optimum running condition is investigated in the sense of minimizing the criterion function. Experiments showed that the heat balance equation derived for the temperature variation and the estimation of the time constant of the refrigerated system are appropriate. By conclusion, if a proper weighting factor D is selected, the optimum conditions exist for the refrigerating capacity, running hour, and operating cycle in the on-off temperature control of the refrigerating system.