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Numerical Analysis of Combustion in Gasoline Compression Ignition Engines

Authors: Koudai Yoshizawa; Atsushi Teraji; Eiji Aochi; Masaaki Kubo; Shuji Kimura;

Numerical Analysis of Combustion in Gasoline Compression Ignition Engines

Abstract

<div class="htmlview paragraph">A new auto-ignition combustion model for performing multi-zone engine cycle simulations has been developed to investigate the characteristics of compression ignition combustion in gasoline engines. In this combustion model, the auto-ignition timing is predicted with a modified shell model and combustion speed is calculated with a three-region (burned, ignited and unburned) model. Engine cycle simulations performed with this model were used to analyze the effect of engine operating parameters, i.e., temperature and air-fuel distributions in the cylinder, on combustion characteristics. It was found that the air-fuel distribution in the cylinder has a large impact on combustion characteristics and knocking was prevented by creating a fuel-rich zone at the center of the cylinder under high load conditions. The fuel-rich zone works as an ignition source to ignite the surrounding fuel-lean zone. In this way, two-step combustion is accomplished through two separate auto-ignitions. Based on these results, this paper discusses the possibility of obtaining stable auto-ignition combustion in a gasoline engine at high loads without any knocking.</div>

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Average
Top 10%
Average
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