CAREER: Integrated Modeling and Control of Aftertreatment Systems for Clean, Efficient and High-Performing Gasoline Direct Injection Engines

Clemson University, Clemson SC

Investigators

Abstract

This Faculty Early Career Development (CAREER) project will enable future vehicles to benefit from the improved efficiency and performance of gasoline direct injection (GDI) engines, without suffering from increased soot emissions. An integrated approach is necessary because engine operating conditions determine oxygen and fuel content and temperature of the exhaust gas, which influence the output of the catalytic converter, which in turn governs soot accumulation and oxidation in particulate filters. While the dynamics of diesel engine particulate filters are well understood, particulates produced in GDI engines have substantially different characteristics. Particulate emissions are associated with many adverse health effects, including decreased lung function in both children and adults. As the number of vehicles using GDI engines increases, the need to safeguard public health by mitigating particulate emissions becomes an urgent social concern. Thus this project addresses urgent technological and societal needs. Integration of research and education will be pursued through development of a new graduate course on advanced aftertreatment systems modeling and control, a social media-based discussion group, and a new course for the Clemson Creative Inquiry program. The relationships established in the course of this research will support development of an international research and education program on fundamental modelling and control in exhaust gas aftertreatment systems. This project will enable new exhaust gas aftertreatment technologies for GDI engines, based on a transformative modeling framework at the intersection of macroscale modeling, numerical simulations and optimization theory. System-level models of the engine, catalytic converter, and gasoline particulate filter will be integrated across length scales, incorporating effects ranging from clogging and regeneration of the filter pores, to continuum gas flow in the exhaust manifold. The framework will enable formulation of low-order models of aftertreament systems suitable for real-time optimization-based control, based on systematic and rigorous reduction of continuum models while maintaining accuracy and fidelity. This project will substantially improve macro-scale representations of soot layer physical properties and pore-scale loading and regeneration phenomena in particulate filters. The results will be used to design physics-based estimators for robust control of advanced aftertreament systems.