The development of next-generation hydrogen-fueled engines introduces critical challenges related to thermal loads within the combustion chamber, particularly in high-performance applications. To address the extreme temperatures encountered, effective piston cooling strategies, such as oil jet impingement, are essential. Accurately predicting thermal stresses to prevent component failure is therefore crucial. However, numerical simulations often come with significant computational costs.
This paper presents a comprehensive multi-fidelity modeling approach to predict the thermal behavior of pistons under these demanding conditions. The model integrates a simplified 3D thermal representation of the piston, a lumped-parameter mechanical model of the piston-liner assembly, and convective boundary conditions obtained at various levels of fidelity, from high-level Computational Fluid Dynamics (CFD) simulations to literature correlations. Additionally, the study examines the influence of different approaches to defining boundary conditions on the model’s predictive capability. Calibration of the model was achieved using experimental temperature measurements obtained by sampling residual surface hardness at 8 points on the piston crown after prolonged stationary operation at maximum power in a conventional naturally aspirated high-performance gasoline engine test case.
The results demonstrate a strong correlation between experimental data and numerical predictions, validating the model's accuracy. Additionally, the study investigates the influence of piston crown thickness and the positioning of the cooling oil injection point on the maximum temperatures reached during operation. Findings reveal the critical role of both geometric design and cooling strategies in optimizing thermal performance. This work provides a robust, flexible, and affordable simulation framework for evaluating piston thermal behavior, contributing to the design of reliable engines capable of withstanding extreme thermal conditions.