Modelling of particle size distributions produced by a Diesel engine fueled with different fossil and renewable fuels under like urban and extra-urban operating conditions. (1st March 2020)
- Record Type:
- Journal Article
- Title:
- Modelling of particle size distributions produced by a Diesel engine fueled with different fossil and renewable fuels under like urban and extra-urban operating conditions. (1st March 2020)
- Main Title:
- Modelling of particle size distributions produced by a Diesel engine fueled with different fossil and renewable fuels under like urban and extra-urban operating conditions
- Authors:
- Martos, Francisco J.
Soriano, José A.
Dorado, María P.
Soto, Felipe
Armas, Octavio - Abstract:
- Graphical abstract: Highlights: Predictive semi-experimental model of diesel particle size distributions is proposed. Model proposed also predicts the mean size of soot agglomerates. Model has been validated with different fuels under different operating conditions. Abstract: The use of particle filters, both in diesel and gasoline engines, is increasingly widespread, it being the most used way to reduce the emission of this pollutant into the atmosphere. Predictive knowledge of particle size distributions, both under different operating modes or with fuels of different origin, is increasingly important and necessary. The predictive knowledge of particle distribution is a key factor when it comes to understanding the efficiency of filters and the reactivity of retained particulate matter and thereby helping the design of the regeneration processes of these filters during the lifetime of the vehicle, with the lowest fuel consumption. This work presents a phenomenological model of prediction of particle size distributions under different operating modes, typical of the urban driving conditions with four different fuels, two of fossil origin: diesel without biodiesel and gas-to-liquid derived from natural gas and two of renewable origin: biodiesel (mixture of palm and soy biodiesel) and farnesane (obtained by means of biotechnological processes of sugarcane sub-products). The results show a very good ability of the model to reproduce the particle size distributions at theGraphical abstract: Highlights: Predictive semi-experimental model of diesel particle size distributions is proposed. Model proposed also predicts the mean size of soot agglomerates. Model has been validated with different fuels under different operating conditions. Abstract: The use of particle filters, both in diesel and gasoline engines, is increasingly widespread, it being the most used way to reduce the emission of this pollutant into the atmosphere. Predictive knowledge of particle size distributions, both under different operating modes or with fuels of different origin, is increasingly important and necessary. The predictive knowledge of particle distribution is a key factor when it comes to understanding the efficiency of filters and the reactivity of retained particulate matter and thereby helping the design of the regeneration processes of these filters during the lifetime of the vehicle, with the lowest fuel consumption. This work presents a phenomenological model of prediction of particle size distributions under different operating modes, typical of the urban driving conditions with four different fuels, two of fossil origin: diesel without biodiesel and gas-to-liquid derived from natural gas and two of renewable origin: biodiesel (mixture of palm and soy biodiesel) and farnesane (obtained by means of biotechnological processes of sugarcane sub-products). The results show a very good ability of the model to reproduce the particle size distributions at the engine cylinder outlet, independently of the engine mode tested and/or the fuel used. … (more)
- Is Part Of:
- Fuel. Volume 263(2020)
- Journal:
- Fuel
- Issue:
- Volume 263(2020)
- Issue Display:
- Volume 263, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 263
- Issue:
- 2020
- Issue Sort Value:
- 2020-0263-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-03-01
- Subjects:
- Particle size distribution function -- Soot -- Compression ignition engines -- Semi-empirical modelling
Fuel -- Periodicals
Coal -- Periodicals
Coal
Fuel
Periodicals
662.6 - Journal URLs:
- http://www.sciencedirect.com/science/journal/latest/00162361 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.fuel.2019.116730 ↗
- Languages:
- English
- ISSNs:
- 0016-2361
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4048.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12896.xml