Establishing the regularities of correlation between ambient temperature and fuel consumption by city diesel buses
Motor transport is the main consumer of energy resources in most countries. Atmospheric conditions, along with the vehicle design, its technical condition, driver’s skill, road, and transport conditions significantly affect fuel consumption. However, in mathematical modeling, they are often taken into account by average values which can affect the accuracy of the results.
The nature of the relationship between ambient temperature and fuel consumption by city diesel buses was established on the basis of experimental and analytical studies. According to the results of the analysis of experimental data, it was found that this relationship is described by polynomial regressions of the second order. The accuracy of the regression model was confirmed by Fisher’s test for two city routes.
Analytical studies of the effect of air density, rolling resistance, transmission efficiency, and all three factors together on fuel consumption were performed using mathematical modeling using the Physical Emission Rate Estimator methodology. It was found that rolling resistance and transmission efficiency have the greatest impact on fuel consumption. In both cases, the difference between the highest and lowest estimated value was 2.5 %. However, in absolute units, the difference is greater by 0.2 l/100 km for rolling resistance.
The obtained results can be used in mathematical models of vehicle movement, in particular city buses, to take into account the dynamics of changes in fuel consumption depending on the ambient temperature. They will also be useful in mathematical models for determining harmful emissions to calculate fuel consumption at various ambient temperatures
How to cite paper:
Savostin-Kosiak, D., Madziel, M., Jaworski, A., Ivanushko, O., Tsiuman, M., & Loboda, A. (2020). Establishing the regularities of correlation between ambient temperature and fuel consumption by city diesel buses. Eastern-European Journal of Enterprise Technologies, 6(3 (108), 23–32. https://doi.org/10.15587/1729-4061.2020.220257