Coordination Funds

当前用于机动的燃烧系统的显著改进是减少温室气体排放的一个重要方面。研究单位的首要目标是在对循环变化进行系统分析的基础上，为进一步优化现代火花点火（SI）燃烧概念提供基础，从而大大提高效率并减少污染物排放。目前，高度优化的si发动机的工作范围受到不希望发生的燃烧现象的限制，如失火、燃料转换不完全和发动机爆震，这些都受到循环变化的显著影响。减少这些现象出现的策略是存在的，但它们通常会导致热效率降低，从而增加二氧化碳的排放。因此，为了进一步优化si发动机，有必要通过减少循环变化或有针对性地开发以确保高效稳定运行的方式来扩大工作范围。实现这一目标需要对循环变化的根本原因、发展和影响有一个基本的了解。然而，目前，这些既不能完全理解，也不能预测性地描述。利用新颖的实验技术与创新的建模和仿真技术相结合，通过对多尺度因果链进行前向和后向分析，建立对这些现象的详细理解，并开发预测仿真方法。为此，用于分析和验证的数据将从实验和直接数值模拟中生成，从简单的流动到整个发动机循环的不同配置层次。与传统的发动机实验相比，采用高精度激光方法获得的实验数据将是独一无二的，因为将特别关注对数值模拟至关重要的初始条件和边界条件。只有这个层次的细节才能够开发和验证新的和高度精确的建模方法。在这些数据的基础上，混合和燃烧的预测模型将被开发和验证。最后，本文将结合大涡模拟（LES）的实验研究和数值分析，对理想燃油喷射发动机和直喷发动机的循环变化的原因和影响进行研究。目标是对因果链进行系统的向前和向后分析，以表征循环变化，并在实验和模拟的密切相互作用中确定其各种原因。

The significant improvement of present-day combustion systems used for mobility is an important aspect for the reduction of greenhouse gas emissions. The overarching goal of the Research Unit is to provide, based on systematic analysis of cyclic variations, the foundations for a further optimization of modern spark-ignition (SI) combustion concepts, which lead to considerable improvements of efficiency and the reduction of pollutant emissions. Presently, the operation range of highly optimized SI-engines is limited by the occurrence of unwanted combustion phenomena, such as misfire, incomplete fuel conversion, and engine knock, which are all significantly impacted by cyclic variations. Strategies to minimize the appearance of these phenomena exist, but they typically lead to reduced thermal efficiency and hence increased emissions of carbon dioxide. For a further optimization of SI-engines, it is therefore necessary to extend the operation range either by the reduction of cyclic variations or by their targeted exploitation in a way that ensures stable operation at high efficiency. Accomplishing this goal requires a fundamental understanding of the root causes, the development, and the effects of cyclic variations. However, at present, these are neither completely understood nor can they be predictively described. Using novel experimental techniques combined with innovative modeling and simulation technology, a detailed understanding of these phenomena will be established by performing forward and backward analysis of the multi-scale causal chain, and predictive simulation methods will be developed. For this, data for analysis and validation will be generated from experiments and direct numerical simulations for a hierarchy of different configurations from simple flows all the way to full engine cycles. The experimental data, which will be acquired with highly-accurate laser-based methods, will be unique compared with conventional engine experiments, since special attention will be devoted to initial and boundary conditions, which are of critical importance for numerical simulations. Only this level of detail will enable development and validation of new and highly accurate modeling approaches. On the basis of these data, predictive models for mixing and combustion will be developed and validated. Finally, cause and effect of cyclic variations both for idealized port-fuel-injected and for direct-injected SI-engines will be investigated by a combination of experimental studies and numerical analyses using large-eddy simulations (LES). The goal is the systematic forward and backward analysis of the causal chain to characterize cyclic variations and to identify their various causes in a close interaction of experiment and simulation.