Oil jets piston cooling: A numerical methodology for the estimation of heat transfer coefficients and optimization of the piston temperature field through a genetic algorithm

Abstract

High-efficiency internal combustion engines need specific methodologies to be developed for the design improvement of the components. Predicting and reducing the thermal loadings on the parts are critical tasks to be addressed. This contribution focuses on the thermal management of the piston through oil jets. The operating temperature of the piston deeply affects its thermo-mechanical behavior, thus possibly jeopardizing the structural integrity of the component. The design of piston cooling jets is usually addressed through Computational Fluid Dynamics, which can guarantee accurate results, usually at a high computational cost. In this contribution, a faster tool is derived to grasp the effect of the cooling jets on the temperature of the piston. Empirical correlations are applied to predict the instantaneous heat transfer coefficients on the piston. The reciprocating motion of the piston is considered since it affects the interaction between the surface and the oil jets. Instantaneous coefficients are cycle-averaged and used to estimate the temperature of the piston through a Finite Element thermal analysis. Finally, an optimization code is developed to find the best jet configuration capable to minimize the temperature of the piston. This methodology is a powerful tool to select the optimal oil jet nozzles for piston cooling.