• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.4
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• pp.31-39
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• 2010

Although driving patterns strongly influence greenhouse gas and air pollutant emission rate from light duty vehicles, emission measurements have been mainly based on chassis dynamometer testing with one standard driving pattern. And there has been limited work on quantifying the independent effect of driving parameters on emission rate because of multidimensional nature of real-world driving pattern. The objective of this study is to obtain the quantitative effect of relative positive acceleration (RPA) on vehicle emission rate. RPA has been used to define the occurrence of acceleration demanding large amounts of power in certain driving distance and shown to be a significant affecting parameter for real-world emission rate. 40 driving patterns have been developed with fixed driving parameters to investigate independent effect of RPA. For the same values of average vehicle speed and power, the trend in carbon dioxide emission rate and fuel consumption with respect to RPA is very clear. Emission rate of nitrogen oxide and particulate matter also increase with respect to RPA, but the trend is less clear. Carbon dioxide emission from diesel vehicle appear to be more affected by high accelerations compared to that from gasoline vehicle because of high intake air restriction during acceleration caused by turbocharger and intercooler. The results have implications for the possible reduction of environmental effects through better traffic planning and management, driver education and car design.

• Journal of Climate Change Research
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• v.4 no.4
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• pp.359-369
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• 2013

In this paper, correlations between driving parameters and $CO_2$ of light-duty vehicles have been analyzed. Three test vehicles equipped with PEMS (Portable Emission Measurement System) have been driven in real-road in urban areas of Seoul. Averaged vehicle speed, RPA(Relative Positive Acceleration) and stop ratio have been selected as main driving parameters. The analysis have been conducted in interrupted and uninterrupted road types. Averaged values in various driving conditions have been calculated with distance based moving averaging window method. The multiple linear regression method have been applied to account for correlation between driving parameters and $CO_2$ emissions. This approach has shown statistically that $CO_2$ emission per distance (g/km) have tendencies to be increased as decreased averaged vehicle speed and increased RPA and stop ratio. Compared with uninterrupted traffic, interrupted traffic have shown the lower vehicle speed and the higher RPA and stop ratio. These characteristics of driving parameters in interrupted traffic should cause the higher $CO_2$ emission per distance.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.6
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• pp.745-756
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• 2013

The purpose of this study is to evaluate representativeness of fuel-based emission factors. Twelve light-duty diesel vehicles which meet Euro-3 to 5 legislative emission limits were selected for emission tests. Second-by-second modal emission rates of vehicles were measured on a standard laboratory chassis dynamometer system. An off-cycle driving cycle was developed as a representative Korean real-world on-road driving cycle. Fuel-based emission factors were developed for short trip segments that involved in the selected driving cycle. Each segment was defined to have unit travel distance, which is 1 km, and characterized by its average speed and Relative Positive Acceleration (RPA). Fuel-based $NO_x$ emission factors demonstrate relatively good representativeness in terms of vehicle operation conditions. $NO_x$ emission factors are estimated to be within ${\pm}20%$ of area-wide emission factor under more than 40% of total driving situations. This result implies that the fuel-based $NO_x$ emission factor could be practically implemented into the on-road emission management strategies, such as a remote sensing device (RSD). High emitting vehicles as well as high emitting operating conditions heavily affect on the mean values and distributions of CO and THC emission factors. Few high emitting conditions are pulling up the mean value and biasing the distributions, which weaken representativeness of fuel-based CO and THC emission factors.

• Journal of ILASS-Korea
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• v.23 no.4
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• pp.234-243
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• 2018

Since September 2017, a small diesel vehicle certification test mode has been enhanced from NEDC to WLTC. The main reason for the change of the certification test mode is that the certification test mode of the emission control standard of the diesel vehicle does not sufficiently reflect various driving patterns of the actual roads. Several automakers have developed after-treatment systems such as LNT, SCR, and DPF to meet enhanced emissions regulations. In this study, four small diesel cars were selected for sale in Korea, and the exhaust gas measurement test was performed in the WLTC mode, which reflects the driving characteristics of the actual roads. As a result of test, LNT vehicle exceeded Euro 6 NOx regulation and SCR vehicle satisfied Euro 6 NOx regulation. In addition, both LNT and SCR systems showed high NOX emission characteristics due to speed, RPA and Vxa. For the PN, all test vehicles were fitted with a DPF and met the Euro 6 PN regulations, with similar PN emissions results in LNT and SCR system.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.5
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• pp.506-517
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• 2012

Electronic Toll Collection System (ETCS), so called "Hi-Pass" in Korea, has improved traffic flow at toll gate of highways. It is known that the improvement of traffic flow should reduce air pollutants and $CO_2$ from vehicles. In this study, real driving emission of a light duty truck with Portable Emission Measurement System(PEMS) has been measured to evaluate the emission reduction effect due to ETCS. The correlations between driving variables and emissions have been analyzed to verify its effect on traffic flow improvement and emission reduction at toll gate. We considered average vehicle speed, Relative Positive Acceleration (RPA), and the distance of queue as driving variables. Compared to passing Manual Toll Collection System (MTCS) lane without queue, ETCS was able to reduce 38.7% of $NO_x$, 21.6% of soot, and 27.7% of $CO_2$. The results showed that the higher the average vehicle speed, the lower RPA and no queue in ETCS contributed to the emission reductions. Linear equation models with RPA and queue have been established by the multiple linear regression method. The linear models resulted in the higher coefficient of determination than those with only average vehicle speed used for establishing vehicle emission factors.