Estimation of Fuel Consumption through PID Signals Using the Real Emissions Cycle in the City of Quito, Ecuador

Paúl Andrés Molina Campoverde ()
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Paúl Andrés Molina Campoverde: Grupo de Investigación en Ingeniería Del Transporte (GIIT), Universidad Politécnica Salesiana, Quito 170146, Ecuador

Sustainability, 2023, vol. 15, issue 16, 1-20

Abstract: In Ecuador, according to data from the Ministry of Energy, the internal combustion engine is the largest consumer of fossil fuels. For this reason, it is important to identify and develop proposals in the literature that enable the prediction of vehicle fuel consumption in both the laboratory and on the road. To accomplish this, real driving emissions (RDEs) need to be contrasted against the development of an algorithm that characterizes forces that oppose such proposals. From experimental tests, fuel consumption information was collected through a flow meter connected to the fuel line and the engine’s characteristic curves were obtained through a chassis dynamometer. Then, from the parameter identification data (PID), the most important predictors were established through an ANOVA analysis. For the acquired variables, a neural network was implemented that could predict 99% of the estimates and present a relative error lower than 5% compared to common methods. Additionally, an algorithm was developed to calculate fuel consumption as a function of the gear, inertial forces, rolling resistance, slope, and aerodynamic force.

Keywords: RDE; predictors; emission cycle; fuel consumption; algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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