Prediction by mathematical modeling of the behavior of an internal combustion engine to be fed with gas from biomass, in comparison to the same engine fueled with gasoline or methane
Felipe O. Centeno González,
Khamid Mahkamov,
Electo E. Silva Lora,
Rubenildo V. Andrade and
René Lesme Jaen
Renewable Energy, 2013, vol. 60, issue C, 427-432
Abstract:
The performance of a spark ignition internal combustion engine (SI ICE) fueled with biomass gas (woodgas) is evaluated using an analytical mathematical model. For the evaluation, the model was based on the fuel-air thermodynamic cycle for spark ignition engines, taking into account the composition of woodgas used as fuel, the thermodynamic properties of the fuel supplied, the cylinder geometric characteristics, the engine operational conditions, the effects of heat losses in the cycle through the walls of the cylinders and due to the loss as gas “blow-by”, the influence of dissociation processes during the combustion and the residual gases remaining in the cylinders at the beginning of the compression stroke. The model can predict of the internal temperatures profiles, heat flow, as well as the work and pressure in relation to crank angle. It was used also to evaluate the influence of the rotation speed, the air ratio and the ignition timing on the engine indicated power. It was found that when feeding the engine with woodgas, a power output between 59 and 65% can be obtained, in comparison it's powered by gasoline.
Keywords: Gasification; Internal combustion engine; Biomass; Mathematical modeling (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S096014811300284X
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:60:y:2013:i:c:p:427-432
DOI: 10.1016/j.renene.2013.05.037
Access Statistics for this article
Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides
More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().