Análisis de rendimiento de combustible en vehículos categoría M1 en la ciudad de Sangolquí durante las horas de mayor demanda y su relación con los patrones de conducción a través del análisis de señales PID’s obtenidas a través de OBD II.

Abstract

The city of Sangolquí has experienced a growth in population in recent years, which has led to an increase in vehicular traffic year after year and this is more evident in the historic centre of the city, which has led to the congestion of roads that allow mobility within this sector, affecting vehicle users. In recent years the growth of the vehicle fleet in the country has influenced the generation of traffic in the historic centre of Sangolquí and the proximity to the Sangolquí market has caused an increase in this situation, deteriorating the easy mobility in this sector. For the development of the project, a compilation of data and information will be carried out in order to obtain the theoretical foundations that will help the development of the project, using information found in articles, scientific publications, theses, magazines and websites. The analysis of the PID signals obtained made it possible to identify the circumstances in normal traffic that are involved in the increase of fuel consumption in M1 category vehicles. Through the use of the Coast-Down test by means of on-road test of deceleration of the movement leaving the vehicle at constant speed and in neutral until the vehicle stops due to the opposing forces to the movement, the rolling coefficients fr and the drag coefficient Cx are determined to obtain the technical characteristics of the vehicle by means of longitudinal dynamics. Through acceleration and gear changes, characteristics are established in which the tyre speed is related to the engine speed. Once the speed profiles have been obtained, the stopping times are estimated, in which the vehicles are stopped and where they are influenced by the increase in fuel consumption due to the fact that at low speeds or when the vehicle is stopped, the engine does not generate power. By means of the application of unsupervised learning, the vehicle speed steps are obtained, for which the application of the K-means algorithm was chosen, which relates the characteristics of the nearest neighbours by means of the VSS/RPM ratio to obtain the efficiency of each of the vehicle's gears.