Influence of Driving Style on Fuel Consumption and Pollutant Emissions Through PID's Signals

Paul Molina Campoverde; Juan Molina; Karina Bermeo

doi:10.1109/ETCM58927.2023.10308804

Influence of Driving Style on Fuel Consumption and Pollutant Emissions Through PID's Signals

Research Group in Transportation Engineering (GIIT)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

This study analyzes the influence of driving style on fuel consumption and pollutant emissions of CO, CO₂, HC, and NO_x in the city of Cuenca, Ecuador. The most sold SUV in the area is used for this work. The information is acquired in a non-intrusive way without adding mass to the vehicle through the OBD II port using the PID's data identification parameters while the vehicle drives through urban, rural and highway road sections. The vehicle is driven under different driving styles allowing the engine to operate at all possible engine speeds and load conditions. This study shows that eco-driving, which consists of not making abrupt accelerations and sudden stops, as well as maintaining revolution per minute between 2000 and 2500 rpm and constant speeds, allows emissions such as carbon monoxide CO to be kept at levels of 0.1 g/s. On the other hand, eco-driving on the established route reaches a value of 51.97 g/km, representing 69.38 % of the total consumption of aggressive driving.

Original language	English
Title of host publication	ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting
Editors	David Rivas Lalaleo, Manuel Ignacio Ayala Chauvin
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350338232
DOIs	https://doi.org/10.1109/ETCM58927.2023.10308804
State	Published - 2023
Event	7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023 - Ambato, Ecuador Duration: 10 Oct 2023 → 13 Oct 2023

Publication series

Name	ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting

Conference

Conference	7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023
Country/Territory	Ecuador
City	Ambato
Period	10/10/23 → 13/10/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities
SDG 13 Climate Action

Keywords

driving modes
ecodriving
PID's
polluting emissions

CACES Knowledge Areas

617A Design and Construction of Motor Vehicles, Boats and Aircraft

Access to Document

10.1109/ETCM58927.2023.10308804

Cite this

Campoverde, P. M., Molina, J., & Bermeo, K. (2023). Influence of Driving Style on Fuel Consumption and Pollutant Emissions Through PID's Signals. In D. R. Lalaleo, & M. I. A. Chauvin (Eds.), ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting (ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ETCM58927.2023.10308804

Campoverde, Paul Molina ; Molina, Juan ; Bermeo, Karina. / Influence of Driving Style on Fuel Consumption and Pollutant Emissions Through PID's Signals. ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting. editor / David Rivas Lalaleo ; Manuel Ignacio Ayala Chauvin. Institute of Electrical and Electronics Engineers Inc., 2023. (ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting).

@inproceedings{12afe694eafb469f8b8b1adc6d248f0e,

title = "Influence of Driving Style on Fuel Consumption and Pollutant Emissions Through PID's Signals",

abstract = "This study analyzes the influence of driving style on fuel consumption and pollutant emissions of CO, CO2, HC, and NOx in the city of Cuenca, Ecuador. The most sold SUV in the area is used for this work. The information is acquired in a non-intrusive way without adding mass to the vehicle through the OBD II port using the PID's data identification parameters while the vehicle drives through urban, rural and highway road sections. The vehicle is driven under different driving styles allowing the engine to operate at all possible engine speeds and load conditions. This study shows that eco-driving, which consists of not making abrupt accelerations and sudden stops, as well as maintaining revolution per minute between 2000 and 2500 rpm and constant speeds, allows emissions such as carbon monoxide CO to be kept at levels of 0.1 g/s. On the other hand, eco-driving on the established route reaches a value of 51.97 g/km, representing 69.38 \% of the total consumption of aggressive driving.",

keywords = "driving modes, ecodriving, PID's, polluting emissions",

author = "Campoverde, \{Paul Molina\} and Juan Molina and Karina Bermeo",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023 ; Conference date: 10-10-2023 Through 13-10-2023",

year = "2023",

doi = "10.1109/ETCM58927.2023.10308804",

language = "English",

series = "ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Lalaleo, \{David Rivas\} and Chauvin, \{Manuel Ignacio Ayala\}",

booktitle = "ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting",

address = "United States",

}

Campoverde, PM, Molina, J & Bermeo, K 2023, Influence of Driving Style on Fuel Consumption and Pollutant Emissions Through PID's Signals. in DR Lalaleo & MIA Chauvin (eds), ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting. ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting, Institute of Electrical and Electronics Engineers Inc., 7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023, Ambato, Ecuador, 10/10/23. https://doi.org/10.1109/ETCM58927.2023.10308804

Influence of Driving Style on Fuel Consumption and Pollutant Emissions Through PID's Signals. / Campoverde, Paul Molina; Molina, Juan; Bermeo, Karina.
ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting. ed. / David Rivas Lalaleo; Manuel Ignacio Ayala Chauvin. Institute of Electrical and Electronics Engineers Inc., 2023. (ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Influence of Driving Style on Fuel Consumption and Pollutant Emissions Through PID's Signals

AU - Campoverde, Paul Molina

AU - Molina, Juan

AU - Bermeo, Karina

PY - 2023

Y1 - 2023

N2 - This study analyzes the influence of driving style on fuel consumption and pollutant emissions of CO, CO2, HC, and NOx in the city of Cuenca, Ecuador. The most sold SUV in the area is used for this work. The information is acquired in a non-intrusive way without adding mass to the vehicle through the OBD II port using the PID's data identification parameters while the vehicle drives through urban, rural and highway road sections. The vehicle is driven under different driving styles allowing the engine to operate at all possible engine speeds and load conditions. This study shows that eco-driving, which consists of not making abrupt accelerations and sudden stops, as well as maintaining revolution per minute between 2000 and 2500 rpm and constant speeds, allows emissions such as carbon monoxide CO to be kept at levels of 0.1 g/s. On the other hand, eco-driving on the established route reaches a value of 51.97 g/km, representing 69.38 % of the total consumption of aggressive driving.

AB - This study analyzes the influence of driving style on fuel consumption and pollutant emissions of CO, CO2, HC, and NOx in the city of Cuenca, Ecuador. The most sold SUV in the area is used for this work. The information is acquired in a non-intrusive way without adding mass to the vehicle through the OBD II port using the PID's data identification parameters while the vehicle drives through urban, rural and highway road sections. The vehicle is driven under different driving styles allowing the engine to operate at all possible engine speeds and load conditions. This study shows that eco-driving, which consists of not making abrupt accelerations and sudden stops, as well as maintaining revolution per minute between 2000 and 2500 rpm and constant speeds, allows emissions such as carbon monoxide CO to be kept at levels of 0.1 g/s. On the other hand, eco-driving on the established route reaches a value of 51.97 g/km, representing 69.38 % of the total consumption of aggressive driving.

KW - driving modes

KW - ecodriving

KW - PID's

KW - polluting emissions

UR - https://www.scopus.com/pages/publications/85179514626

U2 - 10.1109/ETCM58927.2023.10308804

DO - 10.1109/ETCM58927.2023.10308804

M3 - Conference contribution

AN - SCOPUS:85179514626

T3 - ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting

BT - ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting

A2 - Lalaleo, David Rivas

A2 - Chauvin, Manuel Ignacio Ayala

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023

Y2 - 10 October 2023 through 13 October 2023

ER -

Campoverde PM, Molina J, Bermeo K. Influence of Driving Style on Fuel Consumption and Pollutant Emissions Through PID's Signals. In Lalaleo DR, Chauvin MIA, editors, ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting. Institute of Electrical and Electronics Engineers Inc. 2023. (ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting). doi: 10.1109/ETCM58927.2023.10308804

Influence of Driving Style on Fuel Consumption and Pollutant Emissions Through PID's Signals

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

CACES Knowledge Areas

Access to Document

Other files and links

Fingerprint

Characterization of Sustainable Mobility Models Using Machine Learning Architectures Applied to PID Signals Obtained via OBD II for the Study of Pollutant Emissions in the City of Cuenca

Cite this

Influence of Driving Style on Fuel Consumption and Pollutant Emissions Through PID's Signals

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

CACES Knowledge Areas

Access to Document

Other files and links

Fingerprint

Projects

Characterization of Sustainable Mobility Models Using Machine Learning Architectures Applied to PID Signals Obtained via OBD II for the Study of Pollutant Emissions in the City of Cuenca

Cite this