Fast Identification of the Failure of Heavy-Duty Diesel Particulate Filters Using a Low-Cost Condensation Particle Counter (CPC) Based System

Abstract

The penetration of diesel particulate filters (DPFs) in the market is growing fast. However, in the current inspection/maintenance (I/M) regulation for these vehicles, particulate emissions were capped with smoke opacity, which is incompetent to identify the excessive particle number (PN) induced by non-major DPF failures such as small cracks in substrate. This research aimed at developing a fast identification method for such malfunctioning vehicles using a low-cost condensation particle counter (CPC). To verify the effectiveness of idle PN test, 33 China-5 and China-6 heavy-duty vehicles fueled with diesel and natural gas (NG) were tested using the regulatory portable emission measurement system (PEMS) as per China-6 protocol and idle PN tests using a low-cost CPC-based system. PN emissions from China-6 vehicles with malfunctioning DPFs were at a similar level to those from China-5 vehicles (without DPF), which were significantly higher than the proper counterparts. Idle PN tests using a CPC-based system managed to identify the vehicles with DPF failures. Volumetric PN concentrations of these vehicles were much higher than those of the proper ones. This study proved that an easy, fast, and low-cost procedure could be used to screen out those high emitters with DPF failure.

Evaluation of Measurement Procedures for Solid Particle Number (SPN) Measurements during the Periodic Technical Inspection (PTI) of Vehicles

“…When the DPF is removed or broken >5 × 10 6 #/cm 3 concentrations are expected [20,22,23]. Similar low idling concentration ranges were found also for heavy duty vehicles [24,25]. A study compared SPN-PTI with opacity measurements for 300 vehicles and found that for a SPN-PTI limit of 2.5 × 10 5 #/cm 3 the 15% of the vehicles would have failed when less than 1% of the tested vehicles failed the currently applied opacity test [15].…”

Development of Vehicle Emission Model Based on Real-Road Test and Driving Conditions in Tianjin, China

“…The modeling idea of the emission model based on driving conditions is to take the mathematical law embodied between the measured emission data and the "substitute parameters" as the core, and then use a mathematical means such as statistical regression to fit the mathematical function closest to the law [18]. In order to more accurately express the relationship, the emission model based on driving conditions will also rely on the physical relationship between vehicle emission and "substitute parameters" when establishing the mathematical function [19]. Furthermore, in recent years, with the continuous maturity of real road vehicle test methods and the rapid development of portable exhaust measurement technology, especially the improvement of measurement accuracy, so that it becomes more and more feasible to monitor the micro and transient emission characteristics of vehicles under real road driving conditions and to develop local emission models accordingly [19].…”