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A Comparison on Emission Characteristics between Passenger Car Using Gasoline (Including HEV) and Diesel Fuel according to the Various Test Mode
Technical Paper
2019-01-1408
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
In the whole world, emission regulations for vehicles with internal combustion engine have been dramatically strengthened to reduce air pollutions of urban area. Recently, SULEV and EURO-6 emission standard were applied to the gasoline and diesel vehicles in Korea, respectively. Therefore, emission characteristics on passenger car using gasoline including HEV and diesel fuel according to the various test modes were conducted in this study. In order to this investigation, exhaust emission characteristics of gasoline and diesel vehicles were measured and analyzed by using chassis dynamometer (Chassis dynamometer 48˝compact 2WD, AVL) and emission analyzer (MEXA-7000 series, Horiba). Test vehicles were selected the 3 domestic models of a car in Korea. For analysis on emission characteristics according to driving cycles including certification mode, NEDC, FTP-75 and WLTP modes was applied. From these results, it can be shown that all test vehicle models meet the emission standard. In the diesel vehicles, NOx emission in FTP-75 and WLTP mode dramatically increased compared to NEDC mode. CO2 emission of gasoline vehicles have higher level than that of diesel vehicles. Also, CO2 emissions shows large value that of WLTP, FTP-75 and NEDC in order.
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Authors
- Hyung Jun Kim - National Institute of Environmental Research
- Jong Tae Lee - National Institute of Environmental Research
- Yunsung Lim - National Institute of Environmental Research
- Jihoon Keel - National Institute of Environmental Research
- Youdeug Hong - National Institute of Environmental Research
- Hyun Gu Roh - Induk University
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Citation
Kim, H., Lee, J., Lim, Y., Keel, J. et al., "A Comparison on Emission Characteristics between Passenger Car Using Gasoline (Including HEV) and Diesel Fuel according to the Various Test Mode," SAE Technical Paper 2019-01-1408, 2019, https://doi.org/10.4271/2019-01-1408.Data Sets - Support Documents
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References
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