The impact of driving conditions on light-duty vehicle emissions in real-world driving
To accurately estimate the effect of driving conditions on vehicle emissions, an on-road light-duty vehicle emission platform was established based on OEM-2100TM, and each second data of mass emission rate corresponding to the driving conditions were obtained through an on-road test. The mass emissi...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Vilnius Gediminas Technical University
2020-09-01
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| Series: | Transport |
| Subjects: | |
| Online Access: | https://journals.vgtu.lt/index.php/Transport/article/view/12168 |
| _version_ | 1819124867145924608 |
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| author | Dong Guo Jinbao Zhao Yi Xu Feng Sun Kai Li Juan Wang Yuhang Sun |
| author_facet | Dong Guo Jinbao Zhao Yi Xu Feng Sun Kai Li Juan Wang Yuhang Sun |
| author_sort | Dong Guo |
| collection | DOAJ |
| description | To accurately estimate the effect of driving conditions on vehicle emissions, an on-road light-duty vehicle emission platform was established based on OEM-2100TM, and each second data of mass emission rate corresponding to the driving conditions were obtained through an on-road test. The mass emission rate was closely related to the velocity and acceleration in real-world driving. This study shows that a high velocity and acceleration led to high real-world emissions. The vehicle emissions were the minimum when the velocity ranged from 30 to 50 km/h and the acceleration was less than 0.5 m/s2. Microscopic emission models were established based the on-road test, and single regression models were constructed based on velocity and acceleration separately. Binary regression and neural network models were established based on the joint distribution of velocity and acceleration. Comparative analysis of the accuracy of prediction and evaluation under different emission models, total error, second-based error, related coefficient, and sum of squared error were considered as evaluation indexes to validate different models. The results show that the three established emission models can be used to make relatively accurate prediction of vehicle emission on actual roads. The velocity regression model can be easily combined with traffic simulation models because of its simple parameters. However, the application of neural network model is limited by a complex coefficient matrix.
First published online 19 March 2020 |
| first_indexed | 2024-12-22T07:31:04Z |
| format | Article |
| id | doaj.art-397f72a0b6784760999ee23443f4cd78 |
| institution | Directory Open Access Journal |
| issn | 1648-4142 1648-3480 |
| language | English |
| last_indexed | 2024-12-22T07:31:04Z |
| publishDate | 2020-09-01 |
| publisher | Vilnius Gediminas Technical University |
| record_format | Article |
| series | Transport |
| spelling | doaj.art-397f72a0b6784760999ee23443f4cd782022-12-21T18:34:02ZengVilnius Gediminas Technical UniversityTransport1648-41421648-34802020-09-0135437938810.3846/transport.2020.1216812168The impact of driving conditions on light-duty vehicle emissions in real-world drivingDong Guo0Jinbao Zhao1Yi Xu2Feng Sun3Kai Li4Juan Wang5Yuhang Sun6School of Transportation and Vehicle Engineering, Shandong University of Technology, ChinaSchool of Transportation and Vehicle Engineering, Shandong University of Technology, ChinaSchool of Transportation and Vehicle Engineering, Shandong University of Technology, ChinaSchool of Transportation and Vehicle Engineering, Shandong University of Technology, ChinaSchool of Transportation and Vehicle Engineering, Shandong University of Technology, ChinaSchool of Transportation and Vehicle Engineering, Shandong University of Technology, ChinaSchool of Transportation and Vehicle Engineering, Shandong University of Technology, ChinaTo accurately estimate the effect of driving conditions on vehicle emissions, an on-road light-duty vehicle emission platform was established based on OEM-2100TM, and each second data of mass emission rate corresponding to the driving conditions were obtained through an on-road test. The mass emission rate was closely related to the velocity and acceleration in real-world driving. This study shows that a high velocity and acceleration led to high real-world emissions. The vehicle emissions were the minimum when the velocity ranged from 30 to 50 km/h and the acceleration was less than 0.5 m/s2. Microscopic emission models were established based the on-road test, and single regression models were constructed based on velocity and acceleration separately. Binary regression and neural network models were established based on the joint distribution of velocity and acceleration. Comparative analysis of the accuracy of prediction and evaluation under different emission models, total error, second-based error, related coefficient, and sum of squared error were considered as evaluation indexes to validate different models. The results show that the three established emission models can be used to make relatively accurate prediction of vehicle emission on actual roads. The velocity regression model can be easily combined with traffic simulation models because of its simple parameters. However, the application of neural network model is limited by a complex coefficient matrix. First published online 19 March 2020https://journals.vgtu.lt/index.php/Transport/article/view/12168on-road emission testdriving conditionslight-duty vehiclevelocityaccelerationmass emission rate |
| spellingShingle | Dong Guo Jinbao Zhao Yi Xu Feng Sun Kai Li Juan Wang Yuhang Sun The impact of driving conditions on light-duty vehicle emissions in real-world driving Transport on-road emission test driving conditions light-duty vehicle velocity acceleration mass emission rate |
| title | The impact of driving conditions on light-duty vehicle emissions in real-world driving |
| title_full | The impact of driving conditions on light-duty vehicle emissions in real-world driving |
| title_fullStr | The impact of driving conditions on light-duty vehicle emissions in real-world driving |
| title_full_unstemmed | The impact of driving conditions on light-duty vehicle emissions in real-world driving |
| title_short | The impact of driving conditions on light-duty vehicle emissions in real-world driving |
| title_sort | impact of driving conditions on light duty vehicle emissions in real world driving |
| topic | on-road emission test driving conditions light-duty vehicle velocity acceleration mass emission rate |
| url | https://journals.vgtu.lt/index.php/Transport/article/view/12168 |
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