Effect of structural parameters on diesel particulate filter trapping performance of heavy-duty diesel engines based on grey correlation analysis

Abstract

Pressure drop and filtration efficiency are important indicators of capture performance of diesel particulate filter (DPF). In this paper, the DPF three-dimensional computational fluid dynamics (CFD) model developed by the three-dimensional software AVL Fire is used to investigate the influence of key structural factors on the capture performance. The results show that the pressure drop in DPF can be reduced by properly increasing the filter diameter, filter length, CPSI or reducing the wall thickness. Increasing the filter diameter, filter length and wall thickness or reducing CPSI in an appropriate range is conducive to improving the DPF filtration efficiency. In addition, based on the results of grey correlation analysis (GRA), the wall thickness, as the most significant structural factor, should be given priority in the design of DPF. This work has important reference value for optimizing DPF capture performance and extending its working time.