Efforts to establish Malaysian urban drive-cycle for fuel economy analysis

Abstract

Emissions from motor vehicles are known to be the major contributor of air pollution. Pollutants that are commonly concerned and regulated for petrol engines are Hydrocarbons, Carbon Monoxide, Nitrogen Oxides and Particulate Matter. One of the most important factor that vary these pollutants is the engine operating condition such as cold start, low engine loads and high engine loads which are found during actual driving. In actual driving conditions, particularly in urban areas, vehicles regularly travel at idle, low or medium speeds which signify the engine part load operations. Thus urban driving carries a crucial weight on the overall vehicle fuel economy. Understanding the implications of urban driving conditions on fuel economy will allow for trategic application of key technologies such as cylinder deactivation in the efforts towards better efficiency. This paper presents the measurement and analysis of engine condition during Malaysian actual urban driving in an attempt to formulate representable fuel consumption data. The measurements were conducted through multiple on-road urban driving with an instrumented 1.6 litre car. Data was collected using the “chase” technique. Driving conditions were recorded over different routes within the selected urban areas, with considerations on the level of population, density and traffic congestion. The on-road driving was performed to measure vehicle speed, engine speed, accelerator pedal traces, engine torque and fuel consumption. The fact that high traffic congestion in urban area dictates the vehicle movements and the engine running conditions were analysed by clustering the variables. The analyses show that idling and cyclic speed ranging up to 25km/h were the most frequent conditions captured in the Malaysian urban driving. Using the cluster analysis, 10 important conditions were identified in developing a framework for the Malaysian actual urban driving conditions, towards representable fuel economy analysis.