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

这一学院早期职业发展(CALEAR)项目将使未来的车辆能够受益于汽油直接喷射(GDI)发动机效率和性能的提高，而不会受到烟尘排放增加的影响。一种综合的方法是必要的，因为发动机的运行条件决定了废气中的氧气和燃料含量以及温度，这影响了催化转化器的输出，而催化转化器反过来又控制着微粒过滤器中的烟尘积累和氧化。虽然柴油发动机微粒过滤器的动力学是众所周知的，但在GDI发动机中产生的微粒具有本质上的不同特征。颗粒物排放与许多不利的健康影响有关，包括儿童和成人的肺功能下降。随着使用GDI发动机的车辆数量的增加，通过减少颗粒物排放来保障公众健康的需要成为一个紧迫的社会问题。因此，该项目满足了迫切的技术和社会需求。将通过开发关于高级后处理系统建模和控制的新研究生课程、基于社交媒体的讨论小组和克莱姆森创造性探究计划的新课程来追求研究和教育的整合。在这项研究过程中建立的关系将支持一个关于废气后处理系统基本建模和控制的国际研究和教育计划的发展。该项目将使新的废气后处理技术成为GDI发动机的新技术，基于一个集宏观建模、数值模拟和优化理论于一体的变革性建模框架。发动机、催化转化器和汽油颗粒过滤器的系统级模型将跨长度尺度进行集成，纳入从过滤器毛孔堵塞和再生到排气歧管中连续气流的各种影响。该框架将使后处理系统的低阶模型能够在保持准确性和保真度的同时，基于连续统模型的系统和严格的简化，形成适用于基于实时优化的控制的低阶模型。该项目将极大地改善颗粒过滤器中烟灰层物理性质以及孔尺度加载和再生现象的宏观尺度表示。这些结果将被用于设计基于物理的估计器，用于先进后处理系统的稳健控制。

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.