Numerical Comparative Study of Fuel Cavitation in Microchannels under Different Turbulence Models

Ziming Li, Zhenming Liu (), Ping Chen, Jingbin Liu and Jiechang Wu
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Ziming Li: College of Power Engineering, Naval University of Engineering, Wuhan 430033, China
Zhenming Liu: College of Power Engineering, Naval University of Engineering, Wuhan 430033, China
Ping Chen: College of Power Engineering, Naval University of Engineering, Wuhan 430033, China
Jingbin Liu: College of Power Engineering, Naval University of Engineering, Wuhan 430033, China
Jiechang Wu: College of Power Engineering, Naval University of Engineering, Wuhan 430033, China

Energies, 2022, vol. 15, issue 21, 1-18

Abstract: The fuel injector is a critical component of the internal combustion engine. The diameters of the injector nozzle and the control chamber’s oil inlet and outlet are generally between 0.2 and 0.5 mm, which are typical microchannel structures. During high-pressure injection, the cavitation phenomenon in the channel seriously affects the reliability of the internal combustion engine. The choice of turbulence and cavitation models is the key to investigate the cavitation in the microchannel by using numerical methods. Based on the Winklhofer microchannel fuel experiment, five representative turbulence models were used to construct a microchannel model, and the results were compared and analyzed with the experiment. The results show that the pressure gradient values obtained from the combination of RNG k-ε and ZGB models were similar to the experimental data, with an error of less than 6%. The cavitation distribution calculated from the combination of LES and ZGB models was most consistent with the experimental observation data. The outlet mass flow rate obtained from the LES and ZGB models matched the trend of the experimental data in the pressure difference range of 19 bar to 85 bar, with an error of less than 2%. For the cross-sectional flow rate calculation, the RNG k-ε and ZGB models had the smallest calculation errors, with errors below 11%.

Keywords: injector; cavitation; microchannel; internal combustion engine; model comparison (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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