Modeling investigation of thermal insulation approaches for Low Heat Rejection Diesel Engines using a Conjugate Heat Transfer Model Journal

Abstract : Heat losses through combustion chamber walls are a well-known limiting factor for the overall efficiency of internal combustion engines. Thermal insulation of the walls has the potential to decrease substantially these heat losses. However, evaluating numerically the effect of coating and of its location in the combustion chamber and then design an optimized combustion system requires the use of high fidelity engine models. The objective of this paper is to present the whole workflow implying the use of three-dimensional computational fluid dynamics (CFD) techniques with conjugate heat transfer (CHT) models to investigate the potential benefits of a coating on a passenger car Diesel engine. First, the baseline combustion system is modeled, using CHT models to solve in a coupled simulation the heat transfers between the fluid in the intake and exhaust lines and in the combustion chamber on one hand, and the solid piston, head and valves on the other hand. Based on this setup, a second simulation is performed, modeling a thermo-swing insulation on all combustion chamber walls by a contact resistance, neglecting its thermal inertia to keep a manageable computational cost. Results show a decrease of 3.3% in fuel consumption with an increase in volumetric efficiency. However, decoupled 1D/3D simulations highlight the inaccuracy of these results and the necessity to model the coating thermal inertia, as they show an over-estimation of the heat insulation rate and, consequently, of the gain in fuel consumption (-2.1% instead of-1.6%), for a coating on the piston with no thermal inertia.
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Adèle Poubeau, Arthur Vauvy, Florence Duffour, Jean-Marc Zaccardi, Gaetano De Paola, et al.. Modeling investigation of thermal insulation approaches for Low Heat Rejection Diesel Engines using a Conjugate Heat Transfer Model Journal. International Journal of Engine Research, SAGE Publications (UK and US), 2019, 20 (1), pp.92-104. ⟨10.1177%2F1468087418818264⟩. ⟨hal-02072985⟩

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