Driving Style Analysis by Studying PID’s Signals for Determination of Its Influence on Pollutant Emissions

Néstor Diego Rivera, Paúl Andrés Molina, Andrea Karina Bermeo, Oscar Enmanuel Bermeo, José Luis Figueroa

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publicationCommunication, Smart Technologies and Innovation for Society - Proceedings of CITIS 2021
EditorsÁlvaro Rocha, Paulo Carlos López-López, Juan Pablo Salgado-Guerrero
PublisherSpringer Science and Business Media Deutschland GmbH
Pages321-331
Number of pages11
ISBN (Print)9789811641251
DOIs
StatePublished - 2022
Event7th International Conference on Science, Technology and Innovation for Society, CITIS 2021 - Virtual, Online
Duration: 26 May 202128 May 2021

Publication series

NameSmart Innovation, Systems and Technologies
Volume252
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

Conference7th International Conference on Science, Technology and Innovation for Society, CITIS 2021
CityVirtual, Online
Period26/05/2128/05/21

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

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