Fleet managers state that fuel consumption accounts for 50% of the operating costs of their cargo and passenger vehicle fleets. Aiming to reduce these costs, transport companies contract telematics services to track their units and monitor fuel consumption along with other variables. The gathered information is used to alert managers on events like excessive fuel consumption, abrupt breaks, and needs for mechanical maintenance. We propose the use of this information to determine the fuel consumption of cargo vehicles at each km of the main roads of a given region and the influence of altitude, road grade, and vehicle age on it. As a case study, we studied the fuel consumption in the main logistic corridor of Colombia, which is characterized by having a highly variable topography. Toward that end, we compared the fuel consumption monitored by a telematics system on 46 vehicles of different cargo capacity with the estimated by an energy balance model and observed that they are highly correlated (R2 greater than 0.99). Then, we used the calibrated model to obtain the km-by-km fuel consumption. This information is used by authorities to obtain a close estimation of the cost of cargo transport, the greenhouse gases emissions and to identify locations with unusual high fuel consumption. Furthermore, the slope of the linear correlation (Cf) decouples the fuel consumption associated with driving style (human factors) from other influencing factors. Then, we observed that the effects of altitude on fuel consumption are negligible.
Bibliographical noteFunding Information:
We thank the Mexican National Council for Science and Technology (Conacyt), the Iberoamerican program of science and technology for the development (CYTED), the Latin American Network for Research in Energy and Vehicles (RELIEVE) for supporting this research project. The authors also thank the contributions of Virginia Nuñez and Fernando Cepeda from the Energy and Climate Change Research Group (GIECC) for their help and collaboration. Finally, the authors acknowledge the collaboration from MSc. Jhon Jairo Pabón from SID Group for his technical inputs.
All Science Journal Classification (ASJC) codes
- Building and Construction
- Mechanical Engineering
- Management, Monitoring, Policy and Law