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Investigating the impact of gasoline lubricity on the high pressure pumps operation
Technical Paper
2019-01-2213
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Ever stringent emissions regulations have led the car manufacturers to optimize the combustion occurring inside Internal Combustion Engines as well as post-treating the emissions coming from the exhaust pipe. In particular, this led in the late 90's to the introduction of high pressure injection systems inside Diesel engines. This created a tricky situation in which at the same time, the state-of-the-art Diesel engines were requiring more lubricity from the fuel (to make the high pressure pump operate in proper conditions) while the lubricity of the fuels were decreasing due to the removal of sulphur & polar compounds. To cope with this, a method for measuring the lubricity of fuels has been developed (i.e. the HFRR test) and the use of lubricity additives became usual.
Lately, as it is the case for Diesel engines, the Gasoline Direct Injection engines are using higher and higher injection pressures. The state of the art GDI engines are currently using injection pressure as high as 500 bar. A lot of work is also currently ongoing on Gasoline Compression Ignition (GCI) engines which use even higher injection pressure (above 1 000 bar). A high injection pressure means that a high pressure pump has to be used and so, proper lubricity has to be brought by the fuel.
In this paper, tests on the lubricity of gasoline have been done using a pump bench test and determined how the pumps operate when fueled with various gasoline formulations using either a high amount of aromatics (typical of a refinery with reforming capacities) or a low amount of aromatics (typical of a refinery equipped with alkylation capacities). It also focused on the effect of an acid-type lubricity additive on the pump operations.
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Thomas, D., Cyrille, C., and Ludovic, M., "Investigating the impact of gasoline lubricity on the high pressure pumps operation," SAE Technical Paper 2019-01-2213, 2019, https://doi.org/10.4271/2019-01-2213.Data Sets - Support Documents
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