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

这个学院早期职业发展（Career）项目将使未来的车辆受益于汽油直喷（GDI）发动机的效率和性能的提高，而不会受到烟尘排放增加的影响。由于发动机的工作条件决定了废气的氧气和燃料含量以及温度，因此需要采用一种综合的方法，这将影响催化转化器的输出，而催化转化器反过来又会影响颗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已经被很好地理解，但在GDI发动机中产生的微粒具有本质上不同的特性。颗粒排放与许多不利健康影响有关，包括儿童和成人肺功能下降。随着使用GDI发动机的车辆数量的增加，通过减少微粒排放来保障公众健康的必要性成为一个紧迫的社会问题。因此，该项目解决了迫切的技术和社会需求。研究和教育的整合将通过开发一门关于高级后处理系统建模和控制的新研究生课程、一个基于社交媒体的讨论小组和克莱姆森创意探究项目的新课程来实现。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。该项目将基于宏观建模、数值模拟和优化理论交叉的变革性建模框架，为直喷发动机提供新的废气后处理技术。发动机、催化转化器和汽油微粒过滤器的系统级模型将在长度尺度上集成，包括从过滤器孔的堵塞和再生到排气歧管中的连续气体流动的影响。该框架将能够制定后处理系统的低阶模型，适用于基于实时优化的控制，基于连续体模型的系统和严格简化，同时保持准确性和保真度。该项目将大大改善颗粒过滤器中煤烟层物理性质和孔隙尺度加载和再生现象的宏观表征。结果将用于设计基于物理的估计器，用于先进后处理系统的鲁棒控制。

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.