Automobile industry is facing challenges in the field of technological innovation and achieving minimum Total Cost of Ownership (TCO) despite rise in fuel prices. To overcome these challenges is certainly a challenging task. In doing so, automobile sector is mainly focused on passenger safety, comfort, reliability, meeting stringent emission norms, and above all reducing the vehicle fuel consumption. Referring to the Paris climate agreement, and India’s commitment to reduce the CO2 intensity by 33% - 35% by 2030 below the 2005 levels [1], it is imperative to lay down strong policies and procedure to curb the fuel consumption to contribute for reduction in carbon foot print and oil imports.
Transportation sector is majorly responsible for the GHG Emission of which the CO2 emission from commercial vehicles is nearly 73% [2], although the total sales of commercial vehicles are around 4% of cumulative vehicle sales. Physical testing of these vehicles for FC measurement is very expensive and laborious task due to number of variants involved in testing. In view of these factors, it is necessary to establish a very robust simulation based methodology for fuel consumption/CO2 monitoring of commercial vehicles with GVW of above 3.5 T. Countries like US, EU, Canada, Japan and China have already moved towards simulation based calculations for CO2 monitoring and certification [3].
This paper illustrates the methodology for CO2 calculation, which is in harmony with the FC prediction and monitoring procedure available in Europe. Strenuous vehicle (air drag test, coast down) testing and component (Engine, Transmission, Differential & Tyres) testing were carried out as per defined methodology to generate the detailed vehicle data to prepare the simulation model in VECTO [4]. The results from VECTO are then compared with the real world fuel consumption measurements.
To make the simulation tool more compatible with Indian driving and road conditions, it is also proposed to develop India specific mission profiles which would bring in a more holistic approach for fuel consumption estimation by simulation