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Experimental investigation and modelling of biodiesel combustion in engines with late direct injection strategy

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URI: http://hdl.handle.net/10498/27053

DOI: 10.1016/j.egyr.2022.05.279

ISSN: 2352-4847

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APC_2022_066.pdf (1.818Mb)
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Author/s
Vélez Godiño, José AntonioAuthority UCA; Torres García, Miguel; Jiménez-Espadafor Aguilar, Francisco José
Date
2022-11
Department
Máquinas y Motores Térmicos
Source
Energy Reports 8 (2022) 7476–7487
Abstract
The combination of alternate fuels, such as biodiesel, and low-temperature combustion (LTC) constitutes a promising solution to reduce pollutant emission and to avoid dependence on fossil fuels. However, this concept requires additional research to optimise LTC of biodiesel over wider operating ranges, specifically including the implementation of numerical models to assist in the development of these engines. In this work, an experimental analysis was carried out assessing both thermal performance and emissions derived from the LTC of diesel/biodiesel blends with late direct injection. Furthermore, this analysis allowed implementing a predictive tool to characterise in-cylinder pressure trace under this operation strategy. This model was coupled with an empirical law to simulate heat release during the combustion process. Least squares method was applied to fit this empirical law to experimental data involving different conditions in terms of percentages of rapeseed biodiesel in the fuel blend, rotational speed, fuel/air equivalence ratio and percentages of external exhaust gas recirculation. To build the predictive model, a multiple regression methodology was used to correlate the law parameters with the operating conditions. Finally, a validation process based on the simulation of in-cylinder pressure trace was developed, revealing that the predictions agreed well with the experimental data. This suggests that the proposed model is able to satisfactorily predict the LTC of diesel/biodiesel blends within the test range.
Subjects
Biofuels; Biodiesel; Brassica napus; Low-temperature combustion; Predictive model
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  • Artículos Científicos [4307]
  • Articulos Científicos Maq. Mot. Térm. [25]
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
This work is under a Creative Commons License Attribution-NonCommercial-NoDerivatives 4.0 Internacional

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