Optimization of a GDI engine operation in the absence of knocking through numerical 1D and 3D modeling. (May 2016)

• Record Type: Journal Article
• Authors: Boccardi, S.; Catapano, F.; Costa, M.; Sementa, P.; Sorge, U.; Vaglieco, B.M.
• Is Part Of: Advances in engineering software. Volume 95(2016)
• Page Start: 38
• Page End: 50
• Publication Date: 2016-05
• Subjects: GDI -- Optimization -- Multi-objective optimization -- CFD modeling -- Energy efficiency -- Knock control; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2016.01.023
• Languages: English
• ISSNs: 0965-9978

Abstract

Abstract: Various solutions are being proposed and adopted by manufactures and researchers to improve the energetic and environmental performance of internal combustion engines within the transportation sector. For automotive spark ignition engines, gasoline direct injection is one of the presently preferred technologies, in conjunction with turbocharging and downsizing. One of the limiting phenomena of this kind of engines, however, still remains the occurrence of knocking, namely the self-ignition of the so-called end-gas zones of the mixture, not yet reached by the flame front. This phenomenon causes strong in-cylinder pressure oscillations, high stress levels and even damage to engine components. Present work focuses on a numerical and experimental study of a turbocharged GDI engine and is aimed at assessing CFD-O (computational fluid dynamics optimization) procedures to be used in the phase of design as a decision making tool for the development of control strategies for a smooth and efficient operation. A preliminary experimental analysis is performed in order to characterize the considered engine and to investigate the phenomenon of knocking that occurs under some circumstances as the spark advance is increased. The collected data are employed to elaborate a predictive criterion for the appearance of this kind of abnormal combustion, as well as to validate both a 1D and a 3D model for the simulation of the engine working cycle. Various numerical optimization procedures are then realized to increase the engine power output and simultaneously avoid conditions leading to undesired self-ignitions. These are either based on the use of a non-evolutionary algorithm or employ a genetic algorithm in the case multiple contrasting objectives are set. The response surface methodology is also explored as a way to reduce the computational effort.