MODELING VEHICULAR FUEL CONSUMPTION FOR PASSENGER CARS UNDER URBAN INTERRUPTED TRAFFIC OPERATING CONDITIONS IN ADDIS ABABA CITY

Abstract

Vehicular fuel consumption is a growing energy, environmental and economic concern for countries around the globe. It is predominantly affected by factors related to road and traffic conditions. The fuel consumption issue is more magnified in urban areas like Addis Ababa due to the existing congested and interrupted traffic operating conditions. However, the problem is less studied at the local level due to the absence of models well confirmed with the local operating condition. Therefore, the purpose of this study is to calibrate and develop fuel consumption models for passenger cars under urban interrupted traffic operating conditions in Addis Ababa city. The study was entirely based on vehicle performance, driving cycle, and trajectory data collected using an OBD-II scanner mounted on a test vehicle. The study also utilized road condition and specification data obtained from a field test and secondary sources. As a part of analyses, the study comprised characterization of the local driving cycle, calibration of HDM-4 fuel consumption model, and development of regression models. The local driving cycle was characterized by average driving speed, positive acceleration, and frequency of complete stop of 20.07 km/hr, 0.28 m/sec2, and 3.54 stops/km, respectively. It was also described by a proportion of idle, cruise, and acceleration time of 33.20, 11.26, and 29.12%, respectively. From the calibration analysis, calibration factors of Kcr2=0.320, Ki=0.551, and Kpea=0.678 were found to adjust the over-prediction of the model. The calibrated model yielded an overall prediction accuracy of RMSE=29.55 mL/km, MAE=19.77 mL/km, and a model bias of PBIAS=1.32%. The sensitivity analysis based on the calibrated model also showed that a unit change on road grade (1.0%) and IRI (1.0m/km) at 40 km/hr increase fuel consumption by 24.24 and 1.5%, respectively. At last, the impact of traffic on fuel consumption was studied using a linear regression model of idle rate, stop rate, driving speed, and PKE of having an adjusted R 2 value of 94.0%. The study also unveiled that vehicular fuel consumption in urban roads is 104.72 and 44.75% sensitive for 5.0 km/hr speed reduction and 0.1 m/s2 increments of PKE, respectively. Finally, it can be concluded that road grade, pavement roughness, and traffic condition are the most influential factors affecting vehicular fuel consumption. Therefore, calibration factors and models resulted from this study can be reliably approaches to investigate these factors and implement energy-efficient measures.