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Erschienen in: Journal of Visualization 4/2019

23.04.2019 | Regular Paper

Analysis of spray variations and macroscopic spray characteristics in a gasoline direct-injection engine at different injection timings

verfasst von: Ashish Bisht, Sachin Kumar Gupta, Mayank Mittal, Harold Schock

Erschienen in: Journal of Visualization | Ausgabe 4/2019

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Abstract

Fuel injection timing for early injection mode at higher loads in a gasoline direct-injection engine is critical for mixture formation, combustion process and emissions. In the present work, the effect of fuel injection timing on cycle-to-cycle spray variations and macroscopic spray characteristics is quantitatively analyzed at wide-open throttle condition with stoichiometric air–fuel ratio. A Mie scattering technique was employed to visualize the liquid phase of the fuel dispersion with early injection timings at 180° before top dead center (BTDC), 210° BTDC and 240° BTDC of compression with fuel pressure of 5 MPa. A quantitative analysis using proper orthogonal decomposition revealed that cycle-to-cycle spray variations were not significant. Comparing different injection timings, results, however, showed that spray variations were slightly higher at injection timing of 240° BTDC compared to injection timings at 210° BTDC and 180° BTDC. Concerning macroscopic characteristics, it was found that the spray tip penetration length was longer at 210° BTDC compared to injection timings at 240° BTDC and 180° BTDC. It was also observed that the spray areas were comparable for different injection timings until about 0.9 ms after the start of injection, but it was enhanced at later time stamps for injection at 240° BTDC compared to injections at 210° BTDC and 180° BTDC.

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Metadaten
Titel
Analysis of spray variations and macroscopic spray characteristics in a gasoline direct-injection engine at different injection timings
verfasst von
Ashish Bisht
Sachin Kumar Gupta
Mayank Mittal
Harold Schock
Publikationsdatum
23.04.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Journal of Visualization / Ausgabe 4/2019
Print ISSN: 1343-8875
Elektronische ISSN: 1875-8975
DOI
https://doi.org/10.1007/s12650-019-00559-4

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