Investigation of Driving Behavior on Performance and Fuel Consumption of Light-Duty Vehicle (original) (raw)
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Keyhole Markup Language LAMDA Learning Algorithm for Multivariate Data Analysis LDCV Light Duty Commercial Vehicle MAF Mass Air Flow mini MPV Mini MultiPurpose Vehicles MLR Multivariable Linear Regression model MOVES Motor Vehicle and Equipment Emission System software MPG Miles per Gallon NEDC New European Driving Cycle NFDA The National Franchised Dealers Association NHTSA US National Highway Traffic Safety Administration OBD On-Board Diagnostic OGL Open Government Licence PAYD Pay as You Drive Plan PEMS Portable Emissions Measurement System PHYD Pay How You Drive PREVIEW Portable Real-Time Emissions Vehicle Integrated Engineering Workstation PROLOGUE Promoting real Life Observations for Gaining Understanding of road user behaviour in Europe RPM Revolutions per Minute RTA Road Traffic Act 26 SA Selective Availability SAE Society of Automotive Engineers SARTRE Social Attitudes to Road Traffic Risk in Europe SMP Sustainable Mobility Project SWOT Strengths, Weaknesses, Opportunities, and Threats SWOV Netherlands Institute for Road Safety Research TRL Transport Research Laboratory TRRL Transport and Road Research Laboratory TWC Three-Way Catalyst UDC Urban Driving Cycle UTC Universal Time Coordinated VISSIM Microscopic Traffic Model software package VITO Flemish Institute for Technological Research VOEM VITO on-the-road emission and energy measurement system VSP Vehicle Specific Power VSP-SFC The Vehicle Specific Power-Specific Fuel Consumption VTI Swedish Road and Traffic Research Institute WBCSD World Business Council for Sustainable Development WHO World Health Organisation WLTC Worldwide Harmonised Light Duty Driving Test Cycle WLTP The Worldwide Harmonised Light Vehicles Test Procedures WMW Wilcoxon-Mann-Whitney U test method Ford Focus Peugeot Bipper Tepee Citroen C1-1.0 VTi Touch 3dr Volkswagen Golf Renault Twingo Dacia Sandero-1.2 Access 5dr
IOP Conference Series: Materials Science and Engineering, 2018
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Despite the recent technological improvements in vehicles and engines, and the introduction of better fuels, road transportation is still responsible for air pollution in urban areas due to the increasing number of circulating vehicles, and their relative travelled distances. We develop a methodology to calculate, in real-time, the consumption and environmental impact of spark ignition and diesel vehicles from a set of variables such as Engine Fuel Rate, Speed, Mass Air Flow, Absolute Load, and Manifold Absolute Pressure, all of them obtained from the vehicle's Electronic Control Unit (ECU). Our platform is able to assist drivers in correcting their bad driving habits, while offering helpful recommendations to improve fuel economy. In this paper we will demonstrate through data mining, to what extent does the driving style really affect (negatively or positively) the fuel consumption, as well as the increase or reduction of greenhouse gas emissions generated by vehicles.
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