Assessment of the Predictive Capabilities of a Combustion Model for a Modern Common Rail Automotive Diesel Engine

Andrea Piano; Federico Millo; Giulio Boccardo; Mahsa Rafigh; Alessandro Gallone; Marcello Rimondi

doi:10.4271/2016-01-0547

The predictive capabilities of an innovative multizone combustion model DIPulse, developed by Gamma Technologies, were assessed in this work for a last generation common rail automotive diesel engine.

A detailed validation process, based on an extensive experimental data set, was carried out concerning the predicted heat release rate, the in-cylinder pressure trace, as well as NOx and soot emissions for several operating points including both part load and full load points.

After a preliminary calibration of the model, the combustion model parameters were then optimized through a Latin Hypercube Design of Experiment (DoE), with the aim of minimizing the RMS error between the predicted and experimental burn rate of several engine operating points, thus achieving a satisfactory agreement between simulation and experimental engine combustion and emissions parameters.

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Assessment of the Predictive Capabilities of a Combustion Model for a Modern Common Rail Automotive Diesel Engine 2016-01-0547

SAE MOBILUS