Diesel Fuel Quality and Particulate Emissions

1996 ◽  
Author(s):  
S. K. Singal ◽  
K. K. Gandhi
Keyword(s):  
Diesel Fuel ◽  
Particulate Emissions ◽  
Fuel Quality

scholarly journals A Comparative Study of Biofuels and Fischer–Tropsch Diesel Blends on the Engine Combustion Performance for Reducing Exhaust Gaseous and Particulate Emissions

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1538
Author(s):  
Felipe Andrade Torres ◽  
Omid Doustdar ◽  
Jose Martin Herreros ◽  
Runzhao Li ◽  
Robert Poku ◽  
...  
Keyword(s):  
Diesel Fuel ◽  
Alternative Fuels ◽  
Internal Combustion Engines ◽  
Road Transport ◽  
Oxidation Catalyst ◽  
Transport Sector ◽  
Particulate Emissions ◽  
Gaseous Emissions ◽  
Fischer Tropsch ◽  
Engine Combustion

The worldwide consumption of fossil hydrocarbons in the road transport sector in 2020 corresponded to roughly half of the overall consumption. However, biofuels have been discreetly contributing to mitigate gaseous emissions and participating in sustainable development, and thus leading to the extending of the commercial utilization of internal combustion engines. In this scenario, the present work aims at exploring the effects of alternative fuels containing a blend of 15% ethanol and 35% biodiesel with a 50% fossil diesel (E15D50B35) or 50% Fischer–Tropsch (F-T) diesel (E15FTD50B35) on the engine combustion, exhaust emissions (CO, HC, and NOx), particulate emissions characteristics as well as the performance of an aftertreatment system of a common rail diesel engine. It was found that one of the blends (E15FTD50B35) showed more than 30% reduction in PM concentration number, more than 25% reduction in mean particle size, and more than 85% reduction in total PM mass with respect to conventional diesel fuel. Additionally, it was found that the E15FTD50B35 blend reduces gaseous emissions of total hydrocarbons (THC) by more than 25% and NO by 3.8%. The oxidation catalyst was effective in carbonaceous emissions reduction, despite the catalyst light-off being slightly delayed in comparison to diesel fuel blends.

Development of Soft Sensor for Diesel Fuel Quality Estimation

2010 ◽  
Vol 33 (3) ◽  
pp. 405-413 ◽  
Author(s):  
N. Bolf ◽  
G. Galinec ◽  
T. Baksa
Keyword(s):  
Diesel Fuel ◽  
Soft Sensor ◽  
Fuel Quality ◽  
Quality Estimation

Onboard Optimisation of Engine Emissions and Consumption According to Diesel Fuel Quality

2012 ◽  
Vol 5 (4) ◽  
pp. 1661-1683
Author(s):  
Eric Hermitte ◽  
Alain Lunati ◽  
Thaddaeus Delebinski
Keyword(s):  
Diesel Fuel ◽  
Fuel Quality ◽  
Engine Emissions

scholarly journals Capillary Sensor with Disposable Optrode for Diesel Fuel Quality Testing

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1980 ◽  
Author(s):  
Michal Borecki ◽  
Przemyslaw Prus ◽  
Michael L. Korwin-Pawlowski
Keyword(s):  
Signal Processing ◽  
Diesel Fuel ◽  
Optoelectronic Device ◽  
Data Series ◽  
Fuel Quality ◽  
Engine Operation ◽  
Quality Classification ◽  
Artificial Neural Network Classifier ◽  
Quality Type

Diesel fuel quality can be considered from many different points of view. Fuel producers, fuel consumers, and ecologists have their own ideas. In this paper, a sensor of diesel fuel quality type, and fuel condition that is oriented to the fuel’s consumers, is presented. The fuel quality types include premium, standard, and full bio-diesel classes. The fuel conditions include fuel fit for use and fuel degraded classes. The classes of fuel are connected with characteristics of engine operation. The presented sensor uses signal processing of an optoelectronic device monitoring fuel samples that are locally heated to the first step of boiling. Compared to previous works which consider diesel fuel quality sensing with disposable optrodes which use a more complex construction, the sensor now consists only of a capillary probe and advanced signal processing. The signal processing addresses automatic conversion of the data series to form a data pattern, estimates the measurement uncertainty, eliminates outlier data, and determines the fuel quality with an intelligent artificial neural network classifier. The sensor allows the quality classification of different unknown diesel fuel samples in less than a few minutes with the measurement costs of a single disposable capillary probe and two plugs.

scholarly journals Biodiesel Production from Four Residential Waste Frying Oils: Proposing Blends for Improving the Physicochemical Properties of Methyl Biodiesel

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4111
Author(s):  
Youssef Kassem ◽  
Hüseyin Çamur ◽  
Ebaa Alassi
Keyword(s):  
Physicochemical Properties ◽  
Diesel Fuel ◽  
Quality Standard ◽  
Biodiesel Production ◽  
Fuel Quality ◽  
Flow Properties ◽  
Frying Oils ◽  
Cold Flow ◽  
Cold Flow Properties ◽  
The Stability

The physicochemical properties of biodiesel fuels and their blends prepared from four residential waste vegetable frying oils (sunflower (FSME), canola (FCME), mixture of sunflower and rapeseed (FSRME) and corn (FSCME)) were evaluated and measured to determine the best blend. The results indicate that the stability of 10 biodiesel blends was above 10 h for 0-month, meeting the stability requirement regulated in EN 14214:2014 by adding FSCME, which depends on the concentration amount of FSCME. Besides, the results showed that all fuel samples did not meet the requirements of diesel fuel standards. Therefore, automobile gasoline is used as an additive to unmixed biodiesel in various concentrations to reduce the kinematic viscosity, density and cold flow properties. The results indicate that BG85 and BG80 have met the mixed pure biodiesel with gasoline fulfilled diesel fuel quality standard. Therefore, the samples with stability above 10 h were mixed with gasoline in 15% and 20% to reduce the cold flow properties and meet the specifications of the diesel fuel standards. Moreover, the effect of long-term storage on the properties of all samples was investigated under different storage conditions. The results indicate that higher storage temperatures and longer storage periods negatively influenced the properties of the fuel samples.

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