用于预测氮氧化物的SCR的共振频率的可读存储介质

• Format: Patent
• Language: Chinese
• Published: 15.11.2022
• Subjects: BLASTING; CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ENGINE PLANTS IN GENERAL; GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR INTERNALCOMBUSTION ENGINES; GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR MACHINES ORENGINES IN GENERAL; HEATING; LIGHTING; MACHINES OR ENGINES IN GENERAL; MECHANICAL ENGINEERING; PHYSICS; STEAM ENGINES; WEAPONS

本发明的主题涉及用于预测氮氧化物的选择性还原催化器SCR的未来共振频率的经过训练的机器学习模型（300）、方法（200、400）和装置（500），该共振频率表示SCR内的还原剂的浓度。该SCR形成机动车辆所配备的内燃发动机的排出气体流的后处理系统的一部分。本发明的一般原理是基于对SCR的共振频率和存在于SCR中的氨浓度之间的相关性的观察。这一观察导致发明者设想使用机器学习来创建经过训练的机器学习模型，以预测SCR的共振频率。在本发明中，经过训练的机器学习模型是所谓的预测模型，其中在一组过去的观察中发现显著的相关性，并且其中寻求将这些相关性推广到尚未观察的情况。 The subject matter of the present invention relates to trained machine-learning models (300), methods (200, 400) and apparatuses (500) allowing a future resonant frequency of a catalyst for selective reduction of nitrogen oxides (SCR) to be predicted, the resonant frequency being representative of a concentration of a reducing agent within the SCR. The SCR forms part of a system for after-treatment of a flow of exhaust gases of an internal combustion engine with which a motor vehicle is provided. The general principle of the invention is based on the observation of correlations between the resonant frequency of an SCR and the concentration of ammonia present within the SCR. This observation led the inventor to envision using machi