Optimization of Control Parameters for a Heavy-Duty CNG Engine via Co-Simulation Analysis Università di Salerno

Format:

Conference/Event

Author/Creator:

Arsie, Arsie, author.

Contributor:

Criscuolo, Ivan

De Simio, Luigi

Iannaccone, Sabato

Conference Name:

SAE 2011 World Congress & Exhibition (2011-04-12 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2011

Summary:

Internal combustion engines for vehicle propulsion are more and more sophisticated due to increasingly restrictive environmental regulations. In case of heavy-duty engines, Compressed Natural Gas (CNG) fueling coupled with Three-Way Catalyst (TWC) and Exhaust Gas Recirculation (EGR) can help in meeting the imposed emission limits and preventing from thermal stress of engine components. To cope with the new issues associated with the more complex hardware and to improve powertrain performance and reliability and after-treatment efficiency, the engine control strategies must be reformulated. The paper focuses on the steady-state optimization of control parameters for a heavy-duty engine fueled by CNG and equipped with turbocharger and EGR. The optimization analysis is carried out to design EGR, spark timing and wastegate control, aimed at increasing fuel economy while reducing in-cylinder temperature to prevent from thermal stress of engine components. The engine is modeled by a 1-D commercial fluid-dynamic code for the simulation of intake and exhaust gas flow arrangement. In order to speed-up the computational time an empirical formulation based on the classical Wiebe function simulates the combustion process. Furthermore, an intensive identification analysis is performed to correlate Wiebe model parameters to engine operation and guarantee model accuracy and generalization even in case of high EGR rate. The optimization analysis is carried out by means of a co-simulation process in which the 1-D engine model is interfaced with a constrained minimization algorithm developed in the Matlab/Simulink® environment. In the paper, modeling approach and identification analysis are presented and the results of the experimental validation versus measured data at the test bench are shown. Furthermore, the optimization results over a set of operating points belonging to the standard European Transient Cycle (ETC) are presented and discussed

Notes:

Vendor supplied data

Publisher Number:

2011-01-0704

Access Restriction:

Restricted for use by site license