Development of driving cycles and a mathematical model for fuel economy characterization of light duty vehicles in Sri Lanka

Abstract

Estimating the fuel consumption of vehicles under varying driving patterns is challenging and lacks a clear theoretical base. The study aims to provide a scientific basis for a better understanding of driving patterns and their influence on the fuel economy performance of in-use light duty vehicles in Sri Lanka. The study encompasses two specific objectives: the development of driving cycles to represent the local driving conditions of selected vehicle types and the development of a mathematical model capable of estimating fuel economy values of different light duty vehicle types under varying driving patterns. The methodology adopted during the study comprises the theoretical development of two local driving cycles: one specifying both 2W and 3W and the other specifying the characteristics of 4W and the development of a mathematical model that can estimate fuel economy values under varying driving conditions. The main findings of the study portray the characteristics of the two driving cycles developed for the Colombo Metropolitan Area: one cycle spans a period of 1499s which is developed to mimic the driving behavior of 4W whereas the other cycle spans a period of 1215s which is dedicated for 2W and 3W. When developing the said two cycles, data has been acquired from 19 major routes comprising 72 route links within the Colombo Metropolitan region. The micro-trip- based method is opted when developing driving cycles. Krigging spatial interpolation has been utilized as the classification technique for micro-trip generation. The mathematical model developed for the fuel economy characterization is undergone two-way validation, i.e., simulation-based validation and the validation based on manufacturer’s data. When validated, the estimation accuracy of the model gets converged to a band between 89.61% to 92.78%. Conclusively, it can be stated that the developed and validated theoretical model can be utilized as a tool to estimate the fuel consumption of different vehicle types under varying driving conditions. Furthermore, it is recommended to refer to the local driving cycles developed to mimic the local driving behavior when using the theoretical model for localized fuel consumption estimations