Experimental Investigation on OBD Signal and PN Emission Characteristics by Damaged-DPF Types of 2.0 L Diesel Vehicle

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Abstract
A diesel particulate filter (DPF) is an exhaust after-treatment device designed to capture and store exhaust particulate matter, such as soot and ash, to reduce emissions from diesel-powered vehicles. A DPF has a finite capacity and typically uses a substrate made of ceramic material that is formed into a honeycomb structure. Diesel particulate filters play an important role in diesel-fueled vehicles. Failure to maintain these filters can have significant consequences for vehicles. In this study, we investigated the failure type in cordierite DPF substrates. In addition, we experimentally characterized the particle number (PN) emission and on-board diagnostics (OBD) signal of a 2.0 L diesel-fueled vehicle generated by three types of DPF failure (crack, melting, and hollow). Specifically, X-ray photography analysis of the cordierite DPF was performed. The PN and OBD signals were assessed via the KD-147 vehicle driving mode and measured using a DMS-500 (PN measurement device) and global diagnosis tool (GDS) scanner (OBD diagnostic device), respectively. X-ray photography was used to characterize the internal structure of the three DPF-failure samples. A key result was that the maximum value of the OBD data, including airflow mass, boost pressure, and VGT actuator, was distinctly different for each DPF sample. The exhaust temperature gradient for the normal DPF and crack-damaged DPF followed the KD-147 driving pattern. This was because there was no volume damage inside the cordierite DPF substrates. However, in the case of the hollow and melting-damaged DPF, the volume inside the cordierite DPF substrates was reduced or the time for the exhaust gas to stay in the DPF substrates was decreased. The melting-damaged DPF continuously emitted the largest number of nanoparticles (of the order of 109 #/cc). This was regardless of the vehicle driving speed in the KD-147 driving mode. Eventually, an OBD-based algorithm to determine whether a DPF is damaged was derived in this study.
Funding Information
  • R&D project (2022) of the Korea Environmental Industry & Technology Institute (grant number: 2020003070001)

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