The accurate prediction and assessment of soot emissions in internal combustion engines play a central role in the development of modern, sustainable powertrains. The modeling of soot requires high-fidelity models capturing both the gaseous soot precursors with suitable mechanisms and an accurate description of all physico-chemical processes related to the solid particulate. Semi-empirical models based on acetylene are frequently used but are limited in covering complex fuel compositions.

For this reason, we present the coupling of a detailed quadrature-based method of moments (QMOM) soot model to a state-of-the-art flow solver for the simulation of gasoline engines. A close coupling with the underlying gas phase and the additional consideration of polycyclic aromatic hydrocarbons (PAHs) as precursors allow an accurate description of the entire cause-and-effect chain. The fully coupled model is then applied in a 3D-CFD simulation of an optically accessible research engine to investigate the formation, growth and oxidation of soot particles. Experimental high-speed measurements of soot- luminescence and extinction were used for validation purposes. Together with all preceding models along the engine cycle, the newly implemented model is used to identify the root cause of the observed soot formation hotspots. Particular emphasis is placed on the effects of soot oxidation.

内燃机碳烟排放的准确预测和评估在现代可持续动力系统的开发中发挥着核心作用。烟灰建模需要高保真模型，以适当的机制捕获气态烟灰前体，并准确描述与固体颗粒相关的所有物理化学过程。基于乙炔的半经验模型经常使用，但在涵盖复杂的燃料成分方面受到限制。

因此，我们提出了将详细的基于正交的矩量法 (QMOM) 烟灰模型与最先进的流动求解器相结合来模拟汽油发动机。与基础气相的紧密耦合以及将多环芳烃 (PAH) 作为前体的额外考虑，可以准确描述整个因果链。然后将全耦合模型应用于光学可访问研究引擎的 3D-CFD 模拟中，以研究形成、生长和烟灰颗粒的氧化。烟灰发光和消光的实验高速测量用于验证目的。新实施的模型与发动机循环中的所有先前模型一起用于确定观察到的烟灰形成热点的根本原因。特别强调烟灰氧化的影响。