Optimization of Vehicles Fuel Efficiency through Route’s Digital Management

Authors

  • Juan Carlos Latorre Boza Author

DOI:

https://doi.org/10.71701/5031k244

Keywords:

Vehicular congestion, fuel consumption, fuel efficiency, additional trip time, traffic, journey, average speed, travel

Abstract

The purpose of this article is to determine the impact on the proper use of vehicular traffic applications, to reduce fuel consumption, due to the relationship between its performance and traffic level on a given route, which affects the travel average speed. In this study, it has been determined that for higher average speed in the travel of the vehicle, there will be a greater performance of gasoline, diesel or other automotive fuels, and therefore, lower consumption of these. This study was made using traffic data in Lima city, which has the highest traffic density in Peru. For this, it was used an experimental methodology; fuel efficiency was established as a dependent variable, determining that there is an inverse relationship between this and the accumulated time, which occurs in vehicles stopped due to dense traffic or excessive traffic lights. It has been concluded that there is a direct impact of traffic level with higher fuel consumption of vehicles. It was established that every minute of traffic delay represents the reduction of fuel efficiency by 66 meters of travel per liter of consumed fuel; this is by taking as a reference a period in which traffic level on a given route is the lowest registered. It is important to highlight that use of applications that allow selecting and using routes with lower traffic density, generates vehicle operations with lower fuel consumption costs, which has an impact on the lower wear of engines, as well as on lower emission of pollutants gases whose reduction is set at 13 %.

Downloads

Download data is not yet available.

References

[1] Aceña, M. (2016). Gestión y control de flotas y servicios

de transporte por carretera. Madrid: Publicep.

[2] Baptista, P., Fernández, C., & Hernández, R. (2008).

Metodología de la investigación. México D.F.: Ultra.

[3] Campos, J., De Rus, G., & Nombela, G. (2003). Economía

del transporte. Barcelona: Antoni Bosch.

[4] Correa, A., Cogollo, J., & Salazar, J. (2010). Evaluación

del efecto de la conducción eficiente en el consumo de

combustible en vehículos de transporte de carga pesada

usando diseño de experimentos. Producción + Limpia

[en línea], (5), 95-104. Recuperado de http://www.scielo.

org.co/scielo.php?script=sci_abstract&pid=S1909-

04552010000100007&lng=e&nrm=iso

[5] Fundación Transitemos (2013). Propuesta de Hoja de

Ruta para una Movilidad y Transporte Sostenible en Lima

y Callao al 2025. Hacia una ciudad para las personas.

Recuperado de https://transitemos.org/wp-content/

uploads/2017/09/Hacia-Una-Ciudad-para-las-PersonasHoja-de-Ruta-al-2025-V-Final1.pdf

[6] González, R. (2005). Los ciclos de manejo, una

herramienta útil si es dinámica para evaluar el consumo

de combustible y las emisiones contaminantes del auto

transporte. Ingeniería Investigación y Tecnología [en línea],

(6), 147-162. Recuperado de http://dx.doi.org/10.22201/

fi.25940732e.2005.06n3.011

[7] Heinz, K., & Klingebiel, M. (2005). Manual de la técnica

del automóvil. Stuttgart: Bosch.

[8] Morales, H. (2006). Ingeniería vial I. Santo Domingo:

Búho.

[9] Pedraza, L., Hernández, C., & López, D. (2012). Control

de tráfico vehicular usando ANFIS. Ingeniare [en línea],

(20), 79-88. Recuperado de https://www.ingeniare.cl/

index.php?option=com_ingeniare&view=d&doc=73/

art08.pdf&aid=306&vid=73&lang=es

[9] Posada, J., & González, C. (2013). Consumo

de combustible en vehículos para transporte

por carretera –modelos predictivos–. Revista

Ingenierías Universidad de Medellín [en línea], (12),

35-46. Recuperado de https://doi.org/10.22395/

rium.v12n23a3

[10] Rafael, M., & Cervantes, J. (2004). La selección

del tren motriz basada en la eficiencia energética

para vehículos de servicio pesado. Ingeniería

Investigación y Tecnología [en línea], (5), 49-

58. Recuperado de http://dx.doi.org/10.22201/

fi.25940732e.2004.05n1.004

[11] Toro, E., Franco, J., & Gallego, R. (2016). Modelo

matemático para resolver el problema de

localización y ruteo con restricciones de capacidad

considerando flota propia y subcontratada.

Ingeniería Investigación y Tecnología [en línea], (17),

357-369. Recuperado de https://doi.org/10.1016/j.

riit.2016.07.006

[12] Weiers, R. (2006). Introducción a la Estadística para

Negocios. México D.F.: Thomson.

Downloads

Published

2019-01-01

Issue

Section

Artículos

How to Cite

Optimization of Vehicles Fuel Efficiency through Route’s Digital Management. (2019). Revista I+i, 13. https://doi.org/10.71701/5031k244