Vincenzo Di Sirio
Development of a Predictive Combustion and Knock Model for Low-Carbon Gasoline Fuel Blends.
Rel. Federico Millo, Luciano Rolando, Andrea Piano. Politecnico di Torino, Master of science program in Mechanical Engineering, 2026
Abstract
Amid the ongoing evolution of the automotive industry, stringent emissions regulations drive the development of fuel formulations, whose intrinsic properties can contribute to reducing CO2 emissions and enhance engine performance. This thesis aims to develop, calibrate and validate a model of a gasoline single cylinder engine, which features a predictive combustion and knock model, using the one-dimensional (1-D) simulation software GT-POWER. The work relies on seven experimental datasets supplied by Shell Technology Centre Hamburg, obtained from test campaigns conducted using two different low-carbon gasoline fuel blends. The primary objective is to establish a unified calibration framework to assess fuel combustion performance.
To this end, the calibration process seeks to identify a single set of model constants that provides the best agreement across all operating points
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