The Effect of Injection Timing and Phasing on the Emission of a Gasoline Single Cylinder Engine

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Performance evaluation of Internal Combustion Engines (ICEs) and setting different emission standards has manifested the importance of pollution reduction as well as the optimal fuel consumption of these engines. Accordingly, the Engine Management Systems (EMS) are utilized which resulted in optimizing the power alongside the decrease in pollutant emission, through preparing the appropriate air-fuel mixture. Engine management systems are nowadays able to provide an accurate air-fuel mixture. However, the performance of Port Fuel Injection (PFI) engines is also highly dependent on the time of fueling operation which is called the fuel injection phase. There are several methods to achieve the fuel injection phase, the most common of which is using the camshaft position sensor. Nevertheless, this issue is still considered as one of the challenges, devoting much of the researchers’ work, in that using camshaft position sensors and similar ones result in increased production costs as well as some complexities in after-sales services. Therefore, this study aimed to design a control algorithm and determine the fuel injection phase as well as identify the moment of inlet valve closure by evaluation of manifold pressure sensor signal of a single-cylinder engine. In the next step, this feature was added to the engine management system and the engine performance was assessed. The results indicated that it is perfectly possible to determine the injection phase through this method. Moreover, to define the effect of this algorithm on emission reduction, the ECE-R40 emission test was held and its results were compared with the emissions level when the engine management system was not equipped with this algorithm. This comparison shows, by using the phase-detection algorithm, the mean carbon monoxide, unburned hydrocarbons, and nitrogen oxides reduced each by 5.9%, 9.4%, and 2.6%, respectively.
Language:
Persian
Published:
Journal of Engine Research, Volume:17 Issue: 65, Winter 2022
Pages:
3 to 20
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