Abstract
This work analyzed the driving style influence on total polluting emissions emitted by an internal combustion vehicle. In this research, the most sold sedan vehicle in Ecuador was used. Parameters used to define the driving style were speed and acceleration; with these information, two styles were classified: normal and aggressive. There are no formal studies in the media about the relationship between pollutant emissions and driving style. Output variables used were vehicle fuel consumption and CO2, CO, HC and NOX pollutant emissions, and as input variables, driving parameters: intake manifold absolute pressure, throttle position, engine speed, speed and the acceleration of the vehicle. It was identified the most important variables such as MAP, TPS, VSS, and RPM with a determination index of 0.97519. Information was acquired by a data logger device, and post-processed using automatic learning techniques was verified a direct relationship between driving style and the polluting emissions, as well as fuel consumption. Therefore, it was verified that a normal driving style can reduce pollutant emissions by up to 22%, for which it is recommended that drivers should avoid sudden acceleration and sudden braking.
| Original language | English |
|---|---|
| Title of host publication | Communication, Smart Technologies and Innovation for Society - Proceedings of CITIS 2021 |
| Editors | Álvaro Rocha, Paulo Carlos López-López, Juan Pablo Salgado-Guerrero |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 321-331 |
| Number of pages | 11 |
| ISBN (Print) | 9789811641251 |
| DOIs | |
| State | Published - 2022 |
| Event | 7th International Conference on Science, Technology and Innovation for Society, CITIS 2021 - Virtual, Online Duration: 26 May 2021 → 28 May 2021 |
Publication series
| Name | Smart Innovation, Systems and Technologies |
|---|---|
| Volume | 252 |
Conference
| Conference | 7th International Conference on Science, Technology and Innovation for Society, CITIS 2021 |
|---|---|
| City | Virtual, Online |
| Period | 26/05/21 → 28/05/21 |
Bibliographical note
Publisher Copyright:© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Keywords
- Artificial neuronal network
- Driving style
- OBD II
- PID
- Pollutant emissions
- Random forest
CACES Knowledge Areas
- 617A Design and Construction of Motor Vehicles, Boats and Aircraft
Fingerprint
Dive into the research topics of 'Driving Style Analysis by Studying PID’s Signals for Determination of Its Influence on Pollutant Emissions'. Together they form a unique fingerprint.Projects
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Characterization of the vehicle fleet through the application of Machine Learning architectures to determine the effects on the society of the Cuenca canton
Rivera Campoverde, N. D. (Col), Montero Salgado, J. P. (PI), Vazquez Salazar, J. S. (Col), Aguilar Romero, A. Y. (Student), Garate Montalvo, D. A. (Student), Contreras Urgiles, R. W. (Col), Bermeo Naula, A. K. (Student), Morocho Guaman, J. E. (Student), Vacacela Romero, J. H. (Student), Bautista Zeas, J. E. (Student), Reinoso Mejia, L. E. (Student), Fernandez Auquilla, E. P. (Student), Chuva Buele, J. H. (Student), Morocho Valdez, E. O. (Student), Carchi Ramon, P. V. (Student), Maldonado Saquisare, R. O. (Student), Neira Vivanco, E. M. (Student), Barrera Lazo, A. A. (Student) & Nieves Merchan, C. A. (Student)
19/07/18 → 3/06/22
Project: Research and Development
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