A Mean Value Model of the Exhaust System with SCR for an Automotive Diesel Engine

2009-24-0131

09/13/2009

Event
9th International Conference on Engines and Vehicles
Authors Abstract
Content
Nowadays requirements towards a reduction in fuel consumption and pollutant emissions of Internal Combustion Engines (ICE) keep on pushing manufacturers to improve engines performance through the enhancement of existing subsystems (e.g.: electronic fuel injection, air systems) and the introduction of specific devices (e.g.: exhaust gas recirculation systems, SCR, …). Modern systems require a combined design and application of different after-treatment devices. Mathematical models are useful tools to investigate the complexity of different system layouts, to design and to validate (HIL/SIL testing) control strategies for the after-treatment management.
This study presents a mean value model of an exhaust system with SCR; it has been coupled with a common rail diesel engine combustion black box model (Neural Network based). So, dedicated models for exhaust pipes, oxidation catalyst, diesel particulate filter and selective catalytic converter are developed. With this model a simulation study on a DOC-DPF-SCR exhaust system is performed, showing a good coherence with experimental data. This model has been intended as a flexible tool to perform the simulation of exhaust system behaviour for after-treatment control and diagnostic strategies development as well as system architecture analysis. On light-duty drive cycle, the behaviour of the after-treatment system applied to an Euro 5 B-segment vehicle is evaluated. The simulations have highlighted the necessity of accurate SCR control strategies to improve the warm-up phase and optimize reactant dosing.
Meta TagsDetails
DOI
https://doi.org/10.4271/2009-24-0131
Pages
11
Citation
Covassin, F., Preziuso, M., De Cesare, M., and Serra, G., "A Mean Value Model of the Exhaust System with SCR for an Automotive Diesel Engine," SAE Technical Paper 2009-24-0131, 2009, https://doi.org/10.4271/2009-24-0131.
Additional Details
Publisher
Published
Sep 13, 2009
Product Code
2009-24-0131
Content Type
Technical Paper
Language
English