Diesel Engine Exhaust Gas Recirculation Technology Based on Machine Learning

Abstract

Recycling technology has the characteristics of high efficiency, recyclability and reuse. At the same time, it can be widely used in industrial production as an environment-friendly technology. At present, the waste gas treatment methods adopted in China mainly include mechanical (heat treatment) or chemical methods. These methods do great harm to the environment. In order to improve the environmental protection of diesel engines, this paper intends to study the application of machine learning in exhaust gas recirculation technology, and propose the method of exhaust gas recirculation technology. This paper mainly uses the experimental method of EGR scheme design and changes the variables to compare the data difference to realize the research on the influence of internal EGR on emission performance and combustion characteristics. The experimental results show that the NOx emissions of the internal EGR scheme are lower than 10/g•h-1 at 2200r/min and 10% load conditions. The internal exhaust gas recirculation technology has great potential to improve the harmful exhaust gas and total fuel emissions of diesel engines.