• International Journal of Highway Engineering
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• v.13 no.3
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• pp.121-129
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• 2011

The purpose of this study is to determine the relationship between observed traffic data and NOx concentrations from not an ideal condition but a real road in real-time. Also we aim to develop an estimation model for NOx emission concentrations due to vehicle exhaust gas, and it can be applied to monitor the degree of air pollution on National Road in real-time. To eliminate outliers which are occurred due to errors of equipments and other variables, we use the robust analysis and develop two models. which are considering and not considering wind impact. The result of this research can be used for understanding present condition of air pollution caused by vehicle exhaust gas and evaluating for environmental effects of transportation policy.

• Journal of Environmental Impact Assessment
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• v.14 no.6
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• pp.427-441
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• 2005

In order to choose proper dispersion model and emission factors suitable in Korea in evaluating the effect of pollutants emitted by the vehicles in highway on nearby area, various road dispersion models and vehicle emission factors were reviewed. With theoretical inter-comparisons of the exiting models for line source, CALINE 3 and CALINE 4 models which were suggested by US EPA were selected as the road dispersion models for further evaluation with the measurement. The emission factors suggested by Korean Ministry of Environment was turned out to be appropriate since the classification of vehicle kinds was simple and easy to apply in Korea. The comparisons of predicted concentrations by CALINE 3 and 4 models with the measurements in flat, fill and bridge road types showed that CO and PM-10 were in good agreements with experiments and the differences between CALINE 3 and 4 models are negligible. The model concentrations of $NO_2$ by CALINE 4 were also in good agreement with the measurement but those by CALINE 3 were over-predicted. The discrepancies in CALINE 3 model were due to rapid decay reaction of $NO_2$ near the highway, which was not included in CALINE 3 model. For the road type with one & two side cutting grounds, the similar patterns as the flat & fill road type for CO, PM10, & $NO_2$ were observed but the number of data for comparison in these cases were not enough to draw the conclusion. These results lead to the conclusion that CALINE4 model is proper in road environmental impact assessment near the highway in flat, fill and bridge road types.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.183-193
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• 2009

Air pollution due to vehicle exhaust gas is considered to be a main contributor to the issues of transportation & environment. Furthermore it is raising concern over life quality and public health and is also perceived as a global issue. This research aims at providing helping hands for both central and local governments to set up and promote efficient atmospheric quality improvement policies, with the help of the travel demand forecasting model and GIS. More specifically, it tries to produce the overall emission level with time and space-based high resolution framework. This research, based on bottom-up approach reflecting vehicular traffic characteristics, suggested an improved approach to estimating emission level, by using a traffic model with a total of vehicular mileage revised by surveyed value and atmosphere model. Summing up, using the method proposed, the improvement of the reliability of the emissions inventory from the mobile pollutions sources is expected by the proposed integrated paradigm of transportation and atmosphere modeling approach as a new alternative.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.65-72
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• 2006

In new generation vehicle technologies, a fuel cell vehicle becomes more important, by virtue of their emission merits. In addition, a fuel cell is considered as a major source to generate the electricity for vehicles in near future. This paper focuses on modeling of not only an electric vehicle and but also a fuel cell vehicle to estimate performances. And an EV cart is manufactured to verify the modeling. Speed, voltage, and current of the vehicle and modeling are compared to estimate them at acceleration test and driving mode test. The estimations are also compared with the data of the Ballard Nexa fuel cell stack. In order to investigate a fuel cell based vehicle, motor and fuel cell models are integrated in a electric vehicle model. The characteristics of individual components are also integrated. Calculated fuel cell equations show good agreements with test results. In the fuel cell vehicle simulation, maximum speed and hydrogen fuel consumption are estimated. Even though there is no experimental data from vehicle tests, the vehicle simulation showed physically-acceptable vehicle characteristics.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.5
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• pp.518-526
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• 2012

The objective of this research was to develop fugitive emission models of HFC-134a (Hydrofluorocarbon-134a) at the operation and disposal stages of passenger cars. It is essential to estimate the emission of HFC-134a from mobile air conditioner (MAC) due to its high Global Warming Potential (GWP) and extensive use as a refrigerant in MAC. The first-order emission model was introduced and the emission rate constant was assumed to be unvaried with time. A commercial recovery station of refrigerants was used to recover the HFC-134a from the MAC. Average emission rate constant and annual emission rate during the operation period of vehicle are estimated to be $0.0538{\pm}0.0092$ (n=21) $yr^{-1}$ and $5.2{\pm}0.6%$, respectively within a confidence interval of 95%. According to the model results, about 50% of HFC-134a would be emitted from the MAC during the 10 years operation of passenger cars. On the other hand, average remaining portion of HFC-134a in the MACs of scrap cars is $58.2{\pm}4.8%$ (n=50) within a confidence interval of 95%, suggesting that over 40% of the initially charged amount could be released fugitively after disposal provided that the HFC-134a would not be properly treated or recycled.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.363-369
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• 2000

Due to environmental problem for reduction in fuel consumption, vehicle emission and etc., many automotive makers are trying to reduce the weight of the vehicle. The most effective way to reduce the weight of vehicle is to use lighter materials, aluminum, plastics. Aluminum Space Frame has many advantages in weight reduction, body stiffness, ease of model change and so on. So, most of automotive manufacturers are attempting to develope Aluminum Space Frame body. For these reasons, we have developed Aluminum Intensive Vehicle based on steel monocoque body with Hyundai Motor Company. We achieved about 30% weight reduction, the stiffness of our model was higher than that of conventional steel monocoque body. In this paper, with optimization using FEM analysis, we could get more weight reduction and body stiffness increase. In the long run, we analyzed by means of simulation using PAM-CRASH to evaluate crush and crash characteristic of Aluminum Intensive Vehicle in comparison to steel monocoque automotive.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.4
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• pp.451-458
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• 2006

Automotive exhaust is suspected to be one of the major reasons of the rapid increase in greenhouse effect gases in ambient air. As the concerns regarding global worming were increased, the pressure on mobile source greenhouse gas (GHG) emission were also increased. Carbon Dioxides contribute over 90% of total GHG emission and the mobile source occupies about 20% of this $CO_2$ emission. In this study, in order to investigate $CO_2$ emission characteristics from gasoline and LPG passenger cars (PC), which is the most dominant vehicle type in Korea, 53 vehicles were tested on the chassis dynamometer. $CO_2$ emissions and fuel consumption efficiency were measured. The emission characteristics by fuel type, model year, mileage, vehicle speed and transmission type were also discussed. Test modes used in this study were NIER 10 modes and CVS-75 mode, which have been used for developing emission factors and testing new vehicles respectively. The results of this study showed that the main factors which have significant influences on the $CO_2$ emissions are fuel type, transmission type, displacement of vehicle and mileage. The correlation between $CO_2$ emission and FE was also determined by comparing $CO_2$ emission and fuel consumption efficiency. The overall results of this study will greatly contribute to domestic greenhouse gas emissions calculation and designing national strategies for climate change.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.247-256
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• 2012

Recently, estimation of greenhouse gas (GHG) emission has continuously emerged as an important global issue. This study compares various statistical methods for estimation of fuel consumption, which is necessary for calculation of GHG emission in road transportation sector. Existing methods have focused on using merely transportation fuel supply or distance traveled for calculation of fuel consumption. Estimates of GHG emission based on fuel supply, however, cannot reflect various vehicle types or model year. This study suggests and compares, from statistical point of view, several methods, which can be applied to estimate fuel consumption of each vehicle, by combining distance traveled and fuel efficiency (mileage), and total fuel consumption of all vehicles. It also suggests practical measures that can reflect vehicle types and model year to suggested methods for future research.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.115-131
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• 2022

Carbon dioxide (CO₂) emissions from the transportation sector in South Korea accounts for 16.5% of all CO₂ emissions, and road transportation accounts for 96.5% of this sector's emissions in South Korea. Hence, constant research is being carried out on methods to reduce CO₂ emissions from this sector. With the emerging use of smart crossings, attempts to monitor individual vehicles are increasing. Moreover, the potential commercial deployment of autonomous vehicles increases the possibility of obtaining individual vehicle data. As such, CO₂ emission research was conducted at five signalized intersections in the Gangnam District, Seoul, using data such as vehicle type, speed, acceleration, etc., obtained from image detectors located at each intersection. The collected data were then applied to the MOtor Vehicle Emission Simulator (MOVES)-Matrix model-which was developed to obtain second-by-second vehicle activity data and analyze daily CO₂ emissions from the studied intersections. After analyzing two large and three small intersections, the results indicated that 3.1 metric tons of CO₂ were emitted per day at each intersection. This study reveals a new possibility of analyzing CO₂ emissions using actual individual vehicle data using an improved analysis model. This study also emphasizes the importance of more accurate CO₂ emission analyses.

• Journal of Drive and Control
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• v.16 no.2
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• pp.80-90
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• 2019

Fuel cell hybrid electric vehicle is an attractive solution to reduce pollutants, such as noise and carbon dioxide emission. This study presents an approach for energy management and control algorithm based on energetic macroscopic representation for a fuel cell hybrid electric vehicle that is powered by proton exchange membrane fuel cell, battery and supercapacitor. First, the detailed model of the fuel cell hybrid electric vehicle, including fuel cell, battery, supercapacitor, DC-DC converters and powertrain system, are built on the energetic macroscopic representation. Next, the power management strategy was applied to manage the energy among the three power sources. Moreover, the control scheme that was based on back-stepping sliding mode control and inversed-model control techniques were deduced. Simulation tests that used a worldwide harmonized light vehicle test procedure standard driving cycle showed the effectiveness of the proposed control method.