Coordination Funds

协调基金

• 批准号: 317803854
• 负责人: Professor Dr.-Ing. Jakob Andert
• 金额: --
• 依托单位: Lehr- und Forschungsgebiet Mechatronik in mobilen Antrieben
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/317803854?language=en
• 关键词: Coordination; Funds

Cycle-based control is the main research approach currently under investigation for controlling low-temperature combustion (LTC). This control, however, only allows the stabilization of the LTC in a very limited operation range. With a cycle-based control, only cycle-integral system dynamics and disturbance variables can be controlled. The chemical-physical processes, which occur on in-cycle time scales, are relevant for the stability and emission generation of the LTC. They cannot be influenced by a cycle based control. Consequently, the research unit is investigating multi-scale control in order to be able to take the smaller, in-cycle time scales into account. It is expected that the stability can be improved, the operation range can be extended significantly, the efficiency can be increased and the pollutant emissions can be reduced. Multi-scale control is an innovative and novel approach to solve this problem. In the research unit the LTC processes PCCI and GCAI are studied. A controller architecture consisting of a combination of cycle-to-cycle control and an in-cycle controller is developed. To account for the complex nonlinear multivariable system dynamics, optimization-based methods based on models of the process are developed and applied. For this purpose, numerical methods for iterative learning nonlinear model-based predictive control (IL-NMPC) developed for cyclic processes are used as a basis. Specifically for the processes, an analysis and evaluation of possible manipulated and controlled variables as well as the allocation of these variables to the different time scales is done. In addition, suitable formulations of the optimization task are also investigated. The controller-internal models are developed for both the GCAI and the PCCI process. Derived from experiments on singlecylinder test benches, physical models and quantitative descriptions of the processes are created. Furthermore, kinetic descriptions of the combustion processes, which are obtained by using surrogate fuels on optimized test laboratories such as reactors and flames, are emphasized. Furthermore, the integration of ion current as a novel sensor concept in the control system is considered. The developed descriptions are transferred into a structure that can be effectively used for realtime control. Furthermore, physically motivated grey box models are to be created for this purpose. Based on physical and system theoretical observations, models for disturbance variables will be developed. Finally, the resulting control algorithms will be validated on engine test benches. Evaluation criteria are the combustion stability, the coverable operation range in which stable operation and transient load profiles can be realized, and the potential for emission reduction and efficiency increase.

基于循环的控制是目前控制低温燃烧（LTC）的主要研究方法。然而，这种控制仅允许LTC在非常有限的操作范围内稳定。在基于周期的控制中，只能控制周期积分系统动态和干扰变量。发生在循环时间尺度上的化学物理过程与LTC的稳定性和排放生成有关。它们不会受到基于周期的控制的影响。因此，研究单位正在研究多尺度控制，以便能够考虑到较小的周期内时间尺度。预计可以提高稳定性，显著扩展操作范围，提高效率，减少污染物排放。多尺度控制是解决这一问题的一种创新和新颖的方法。在研究单元中，对LTC过程PCCI和GCAI进行了研究。一个控制器架构组成的周期到周期的控制和周期内控制器的组合开发。为了解释复杂的非线性多变量系统动态，基于过程模型的基于优化的方法被开发和应用。为此，数值方法迭代学习非线性基于模型的预测控制（IL-NMPC）开发的循环过程作为基础。具体的过程中，可能的操纵和控制变量的分析和评价，以及这些变量的分配到不同的时间尺度。此外，适当的配方的优化任务也进行了研究。开发了GCAI和PCCI过程的内部模型。通过在活塞缸试验台上的试验，建立了该过程的物理模型和定量描述。此外，动力学描述的燃烧过程，这是通过使用替代燃料的优化测试实验室，如反应器和火焰，得到强调。此外，离子电流作为一种新的传感器的概念在控制系统中的集成被认为是。开发的描述被转移到一个结构，可以有效地用于实时控制。此外，出于物理动机的灰箱模型将被创建用于此目的。根据物理和系统理论观测，将建立干扰变量模型。最后，所得到的控制算法将在发动机试验台上进行验证。评价标准是燃烧稳定性、可实现稳定运行和瞬态负荷分布的可覆盖运行范围以及减排和提高效率的潜力。