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Modeling of Unsteady Heat Transfer Phenomena at the Intake Manifold of a Diesel Engine and Its Application to 1-D Engine Simulation
Technical Paper
2017-32-0097
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
In the past two decades, internal combustion engines have been required to improve their thermal efficiency in order to limit hazardous gas emissions. For further improvement of the thermal efficiency, it is required to predict the mass of intake air into cylinders in order to control the auto-ignition timing for CI engines. For an accurate prediction of intake air mass, it is necessary to model the heat transfer phenomena at the intake manifold. From this intention, an empirical equation was developed based on Colburn equation. Two new arguments were presented in the derived formula. The first argument was the addition of Graetz number, where it characterized the entrance region thermal boundary layer development and its effect on the heat transfer inside the intake manifold. As the second argument, Strouhal number was included in order to represent intake valve effect on heat transfer. This study compared experimental data with the present empirical equation, and average error was estimated to be 3.1%, which was significantly improved in comparison with the Colburn equation. Furthermore, derived empirical heat transfer equation was implemented to the intake manifold model of a diesel engine in 1-D engine simulation. The study confirmed the influence of the heat transfer phenomena, and its importance to intake air. At IVC, temperature difference between Colburn equation and derived equation was calculated to be 3.8 K. This corresponded to an advanced auto-ignition timing by 0.78 deg. CA, which gives an estimated improvement of 0.22% when evaluating both the thermal efficiency and CO2 emission.
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Yilmaz, E., Joji, H., Ichiyanagi, M., and Suzuki, T., "Modeling of Unsteady Heat Transfer Phenomena at the Intake Manifold of a Diesel Engine and Its Application to 1-D Engine Simulation," SAE Technical Paper 2017-32-0097, 2017, https://doi.org/10.4271/2017-32-0097.Data Sets - Support Documents
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References
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