Conjugate heat transfer analysis of a high-performance multi-cylinder engine in 3D-CFD

The adoption of downsizing and turbocharging in modern spark ignition engines results in a considerable increase of the thermal loads acting on the components facing the combustion chamber, therefore causing higher thermo-mechanical stresses and abnormal combustion probability, with negative consequences on engine reliability. CAE tools (CFD/FEA) can be used in early design phase to estimate the thermal loads and the thermal field of engine components, with significant reduction of time-to-market compared to conventional product development based on try and error procedures. The aim of this thesis work, conducted at POWERTECH Engineering S.r.l. in collaboration with McLaren Automotive, is the development of a 3D-CFD Conjugate Heat Transfer (CHT) methodology for the characterization of high-performance multi-cylinder spark ignition engine thermal field, with particular emphasis on the piston thermal field. The objective is the development of a methodology to be used in early engine design phases using the commercial 3D-CFD software CONVERGE. The developed methodology consists of 3 steps: 1. analysis of the standalone piston; 2. simulation of the complete engine assembly; 3. iteration among step 1 and 2 to update boundary conditions, until convergence. Step 1 is the main focus of the present thesis and, additionally, initial simulations concerning step 2 were carried out. The standalone piston model results has shown a good qualitative and quantitative agreement with literature data for the predicted thermal field and heat flow distribution among oil, liner and connecting rod. As far as the complete engine model is concerned, the preliminary results have shown a satisfying agreement with experimental and literature data: although there is an overestimation in the predicted thermal field, temperature variations among engine components are qualitatively reproduced by the 3D-CFD CHT model, which is hence able to identify the correct temperature trend.