ARTÍCULO
TITULO

Algorithm for predicting fuel consumption for anhydrous ethanol mixtures in high-altitude cities

Fabricio Espinoza    
Fredy Tacuri    
Wilmer Rafael Contreras Urgiles    
Javier Vázquez    

Resumen

In the present research work, a mathematical model is obtained for predicting specific fuel consumption in a 1.4-liter Otto cycle engine with electronic injection without making modifications, when using as fuel gasoline mixtures with concentrations in volume of 0 %, 25 %, 50 %, 75 % and 100 % of anhydrous ethanol. For the analysis of results, a simplex lattice reticular mixture experiment design was carried out, which was subject to an urban driving cycle in the city of Cuenca at 2558 m above sea level in a roller power bank. The data acquisition and the development of the algorithm were carried out through an analysis of descriptive statistical methods. The validation of the algorithm was performed through residual analysis. As a main result, there is a mathematical model that enables predicting the engine fuel consumption, for ranges of ethanol concentration from 0 % to 100 % in the gasoline without needing to conduct real tests.

 Artículos similares

       
 
Tianao Qin, Ruixin Chen, Rufu Qin and Yang Yu    
Time series prediction is an effective tool for marine scientific research. The Hierarchical Temporal Memory (HTM) model has advantages over traditional recurrent neural network (RNN)-based models due to its online learning and prediction capabilities. G... ver más

 
Alessandro Massaro    
In the proposed paper, an artificial neural network (ANN) algorithm is applied to predict the electronic circuit outputs of voltage signals in Industry 4.0/5.0 scenarios. This approach is suitable to predict possible uncorrected behavior of control circu... ver más
Revista: AI

 
Shun Wang, Jiayan Wang, Zhikang Xu, Ji Wang, Rui Li and Jinliang Dai    
The application of titanium alloy in shipbuilding can reduce ship weight and carbon emissions. To solve the problem of titanium alloy forming, the deformation prediction of titanium alloy line heating based on a backpropagation (BP) neural network and sp... ver más

 
Feifei He, Qinjuan Wan, Yongqiang Wang, Jiang Wu, Xiaoqi Zhang and Yu Feng    
Accurately predicting hydrological runoff is crucial for water resource allocation and power station scheduling. However, there is no perfect model that can accurately predict future runoff. In this paper, a daily runoff prediction method with a seasonal... ver más
Revista: Water

 
Monica Fira, Hariton-Nicolae Costin and Liviu Goras    
We analyzed the possibility of detecting and predicting ventricular fibrillation (VF), a medical emergency that may put people?s lives at risk, as the medical prognosis depends on the time in which medical personnel intervene. Therefore, besides immediat... ver más
Revista: Applied Sciences