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

这个教师早期职业发展（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，而不会增加碳烟排放。综合方法是必要的，因为发动机操作条件决定了废气的氧和燃料含量以及温度，这影响催化转化器的输出，而催化转化器的输出又控制颗粒过滤器中的碳烟积聚和氧化。虽然柴油发动机颗粒过滤器的动力学是很好理解的，但GDI发动机中产生的颗粒具有显著不同的特性。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求成为迫切的社会问题。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先进的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组，以及克莱姆森创意调查计划的新课程来实现。在此研究过程中建立的关系将支持一个国际研究和教育计划的发展，在排气后处理系统的基础建模和控制。该项目将使新的排气后处理技术的GDI发动机，基于一个变革性的建模框架，在宏观建模，数值模拟和优化理论的交叉点。发动机、催化转化器和汽油颗粒过滤器的系统级模型将在整个长度范围内集成，包括从过滤器孔隙的堵塞和再生到排气歧管中的连续气流的影响。该框架将使制定低阶模型的后处理系统适合于实时优化为基础的控制，基于系统和严格的减少连续模型，同时保持精度和保真度。该项目将大大改善烟尘层的物理特性和颗粒过滤器中的孔隙尺度负载和再生现象的宏观尺度表示。结果将被用来设计先进的后处理系统的鲁棒控制的物理为基础的估计。

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.