Single wall diesel particulate filter (DPF) filtration efficiency studies using laboratory generated particles

Effect of regeneration method and ash deposition on diesel particulate filter performance: a review

As countries around the world pay more attention to environmental protection, the corresponding emission regulations have become more stringent. Exhaust pollutants cause great harm to the environment and people, and diesel engines are one of the most important sources of pollution. Diesel particulate filter (DPF) technology has proven to be the most effective way to control and treat soot. In this paper, we review the latest research progress on DPF regeneration and ash. Passive regeneration, active regeneration, non-thermal plasma-assisted DPF regeneration and regeneration mechanism, DPF regeneration control assisted by engine management, and uncontrolled DPF regeneration and its control strategy are mainly introduced. In addition, the source, composition, and deposition of ash are described in detail, as well as the effect of ash on the DPF pressure drop and catalytic performance. Finally, the issues that need to be further addressed in DPF regeneration research are presented, along with challenges and future work in ash research. Over all, composite regeneration is still the mainstream regeneration method. The formation of ash is complex and there are still many unanswered questions that require further in-depth research.

TSF-transformer: a time series forecasting model for exhaust gas emission using transformer

Monitoring and prediction of exhaust gas emissions for heavy trucks is a promising way to solve environmental problems. However, the emission data acquisition is time delayed and the pattern of emission is usually irregular, which makes it very difficult to accurately predict the emission state. To deal with these problems, in this paper, we interpret emission prediction as a time series prediction problem and explore a deep learning model, a time-series forecasting Transformer (TSF-Transformer) for exhaust gas emission prediction. The exhaust emission of the heavy truck is not directly predicted, but indirectly predicted by predicting the temperature and pressure changes of the exhaust pipe under the working state of the truck. The basis of our research is based on real-time data feeds from temperature and pressure sensors installed on the exhaust pipe of approximately 12,000 heavy trucks. Therefore, the task of time series forecasting consists of two key stages: monitoring and prediction. The former utilizes the server to receive the data sent by the sensors in real-time, and the latter uses these data as samples for network training and testing. The training of the network throughout the prediction process is done in an unsupervised manner. Also, to visualize the forecast results, we weight the forecast data with the truck trajectories and present them as heatmaps. To the best of our knowledge, this is the first case of using the Transformer as the core component of the prediction model to complete the task of exhaust emissions prediction from heavy trucks. Experiments show that the prediction model outperforms other state-of-the-art methods in prediction accuracy.

Review of Particle Filters for Internal Combustion Engines

Diesel engines have gradually become one of the main forces in the human transportation industry because of their high efficiency, good durability, and stable operation. However, compared with gasoline vehicles, the high emission of diesel vehicles forces manufacturers to introduce new pollutant control technologies. Although the particulate matter emissions of gasoline vehicles are lower than that of diesel vehicles, with the popularity of gasoline vehicles and the continuous rise of power, the impact of these particles on the environment cannot be ignored. Therefore, diesel particulate filters and gasoline particulate filters have been invented to collect the fine particles in the exhaust gas to protect the environment and meet increasingly stringent emission regulations. This paper summarizes the research progress on diesel particulate filters and gasoline particulate filters at present and comprehensively introduces the diesel particulate filter and gasoline particulate filter from the mechanism, composition, and operation processes. Additionally, the laws and regulations of various countries and the impact of gas waste particulates on the human body are described. In addition, the mechanisms of the diesel particulate filter, gasoline particulate filter, and regeneration were studied. Finally, the prospects and future directions for the development of particle filters for internal combustion engines are presented.

Development of semi-empirical soot emission model for a CI engine

Soot is one of the main harmful emissions of diesel engines that is mainly generated in the reacting fuel jet of diesel injection. Over 99% of the engine-out soot can be filtered by a diesel particulate filter (DPF). However, when the soot load of the DPF is high, a regeneration process that oxidizes the accumulated soot reduces fuel economy. A real-time soot estimation model can contribute to real-time feedback soot control under transient conditions to minimize the engine-out soot emission and frequency of DPF regeneration. A zero-dimensional engine-out soot estimation model for a diesel engine is developed in this study. The semi-empirical soot model considers both the formation and oxidation of soot. In the model, soot formation was correlated with the cross-sectional average equivalence ratio at the lift-off length of the fuel spray. The equivalence ratio at the lift-off length is an indicator of how much air and vaporized fuel are mixed as the fuel reaches the reaction zone. The mass of the injected fuel and combustion duration were also correlated with soot formation. The Nagle and Strickland-Constable mechanism, which calculates the soot oxidation rate was correlated with the soot oxidation in this study. The results of the soot estimation showed an R² of 0.901 and root mean square error of 10.8 mg/m³ for steady-state experimental cases. The engine-out soot model was also combined with the in-cylinder pressure model proposed by the authors, and validated through the transient Worldwide Harmonized Light Vehicles Test Cycle (WLTC) mode. The estimates agreed with the measured soot, with an accumulated soot error of approximately 6% during the WLTC, even without using an in-cylinder pressure sensor. The soot model developed in this study can help minimize tailpipe-out soot emissions and improve fuel economy by influencing the real-time feedback control during transient and frequent DPF regeneration.

4D In-Situ Microscopy of Aerosol Filtration in a Wall Flow Filter

The transient nature of the internal pore structure of particulate wall flow filters, caused by the continuous deposition of particulate matter, makes studying their flow and filtration characteristics challenging. In this article we present a new methodology and first experimental demonstration of time resolved in-situ synchrotron micro X-ray computed tomography (micro-CT) to study aerosol filtration. We directly imaged in 4D (3D plus time) pore scale deposits of TiO2 nanoparticles (nominal mean primary diameter of 25 nm) with a pixel resolution of 1.6 μm. We obtained 3D tomograms at a rate of ∼1 per minute. The combined spatial and temporal resolution allows us to observe pore blocking and filling phenomena as they occur in the filter’s pore space. We quantified the reduction in filter porosity over time, from an initial porosity of 0.60 to a final porosity of 0.56 after 20 min. Furthermore, the penetration depth of particulate deposits and filtration rate was quantified. This novel image-based method offers valuable and statistically relevant insights into how the pore structure and function evolves during particulate filtration. Our data set will allow validation of simulations of automotive wall flow filters. Evolutions of this experimental design have potential for the study of a wide range of dry aerosol filters and could be directly applied to catalysed automotive wall flow filters.

Numerical Simulation of a Wall-Flow Particulate Filter Made of Biomorphic Silicon Carbide Able to Fit Different Fuel/Biofuel Inputs

To meet the increasingly strict emission limits imposed by regulations, internal combustion engines for transport applications require the urgent development of novel emission abatement systems. The introduction of biodiesel or other biofuels in the engine operation is considered to reduce greenhouse gas emissions. However, these alternative fuels can affect the performance of the post-combustion systems due to the variability they introduce in the exhaust particle distribution and their particular physical properties. Bioceramic materials made from vegetal waste are characterized by having an orthotropic hierarchical microstructure, which can be tailored in some way to optimize the filtration mechanisms as a function of the particle distribution of the combustion gases. Consequently, they can be good candidates to cope with the variability that new biofuel blends introduce in the engine operation. The objective of this work is to predict the filtration performance of a wall-flow particulate filter (DPF) made of biomorphic silicon carbide (bioSiC) with a systematic procedure that allows to eventually fit different fuel inputs. For this purpose; a well-validated DPF model available as commercial software has been chosen and adapted to the specific microstructural features of bioSiC. Fitting the specific filtration and permeability parameters of this biomaterial into the model; the filtration efficiency and pressure drop of the filter are predicted with sufficient accuracy during the loading test. The results obtained through this study show the potential of this novel DPF substrate; the material/microstructural design of which can be adapted through the selection of an optimum precursor.

Real-time particulate emissions rates from active and passive heavy-duty diesel particulate filter regeneration

Periodic regeneration is required to clean the diesel particulate filter (DPF) of heavy-duty diesel vehicle. In this study we analyze real-time particulate matter (PM) mass, particle number, and black carbon emissions during steady state driving active and passive diesel particulate filter (DPF) regenerations on a heavy-duty chassis dynamometer. Regeneration PM emissions were dominated by particles with count median diameter<100nm, with the majority <50nm. Results indicate that vehicle activity during DPF loading significantly affects regeneration particulate emissions. Average PM emission rates (gPM/h) from the 2010 MY vehicle were higher than the 2007 MY vehicle during all regeneration conditions in this study. Sequential forced-active regenerations resulted in reduced particulate mass emissions, but not in reduced particle number emissions, suggesting incomplete stored PM removal or effects of after-treatment fuel injection. Black carbon emission factors (EF_BC) were 3.4 and 21 times larger during driving-active regeneration than during a 50 mph steady state cruise with a recently regenerated DPF for the 2007 and 2010 MY vehicle, respectively. Real-time PM emissions rates were lower during passive regeneration of the 2010 MY DPF, suggesting more modern passive regeneration technologies reduce total on-road particulate and ultrafine particulate emissions.

Repeat Fuel Specific Emission Measurements on Two California Heavy-Duty Truck Fleets

The University of Denver repeated its 2013 fuel specific gaseous and particle emission measurements on two California heavy-duty vehicle fleets. In 2015 1456 measurements at the Port of Los Angeles and 694 measurements at the Cottonwood weigh station in northern California were collected. The Port fleet changed little since 2013, increasing the average age (+1.8 years), accompanied by an increase in particle mass (PM) by +266% (0.03 ± 0.01 to 0.11 ± 0.01 gPM/kg of fuel) and black carbon (BC) by +300% (0.02 ± 0.003 to 0.08 ± 0.01 gBC/kg of fuel). Particle number (PN) also increased (1.5 × 10¹⁴ ± 2.5 × 10¹³ to 2.8 × 10¹⁴ ± 2.8 × 10¹³ PN/kg of fuel) by a smaller percentage (+87%). Chassis model year 2008 and 2009 vehicles currently dominate the fleet, accounting for the majority of these increases. The long-haul Cottonwood fleet decreased in fleet age (-0.6 model years), where half the decreases in fuel specific PM (-66%), BC (-65%), and PN (-19%) emissions are due to the newer fleet; an increased fraction of pre-2008 chassis model year vehicles with retrofit diesel particulate filters (DPFs) account for the remaining reductions. These opposing emissions trends emphasize the importance of fully functional DPFs.

Experimental Study on the Influence of DPF Micropore Structure and Particle Property on Its Filtration Process

A single layer filtration system was developed to investigate the filtration and regeneration performance of diesel particle filter (DPF). The particle layer thickness was directly measured online to analyze the different filtration stages. The influence of particle property on particle layer stage performance was also investigated. The results indicate that the filtration velocity can greatly affect the deep bed filtration stage, and the deposited particle layer can be compressed even in very low filtration velocity and higher filtration velocity trends to form denser particle layer. Optimizing the pore structure can effectively shorten the deep bed filtration stage and reduce the pressure drop eventually. An empirical function was proposed to relate the pore structure and the initial increment rate of pressure drop, which presented that reducing the pore size distribution range (3σ) can result in low DPF filtration pressure drop. The filtration stage could be further divided into four stages, and the value of particle layer thickness ranging within 15~20 μm has been found to be critical number for the shift from the transient stage to the cake filtration stage. Particle with large primary diameter and BET surface was beneficial to form loose particle layer.

Three-dimensionally ordered macroporous (3DOM) SiOC on a cordierite monolith inner wall and its properties for soot combustion

Three-dimensionally ordered macroporous (3DOM) SiOC was successfully fabricated on a cordierite monolith, and LaCoO₃ was coated onto the 3DOM SiOC/cordierite. The 3DOM structure produced a positive effect on soot combustion.

Simultaneous reduction of particulate matter and NO(x) emissions using 4-way catalyzed filtration systems

The next generation of diesel emission control devices includes 4-way catalyzed filtration systems (4WCFS) consisting of both NOx and diesel particulate matter (DPM) control. A methodology was developed to simultaneously evaluate the NOx and DPM control performance of miniature 4WCFS made from acicular mullite, an advanced ceramic material (ACM), that were challenged with diesel exhaust. The impact of catalyst loading and substrate porosity on catalytic performance of the NOx trap was evaluated. Simultaneously with NOx measurements, the real-time solid particle filtration performance of catalyst-coated standard and high porosity filters was determined for steady-state and regenerative conditions. The use of high porosity ACM 4-way catalyzed filtration systems reduced NOx by 99% and solid and total particulate matter by 95% when averaged over 10 regeneration cycles. A "regeneration cycle" refers to an oxidizing ("lean") exhaust condition followed by a reducing ("rich") exhaust condition resulting in NOx storage and NOx reduction (i.e., trap "regeneration"), respectively. Standard porosity ACM 4-way catalyzed filtration systems reduced NOx by 60-75% and exhibited 99.9% filtration efficiency. The rich/lean cycling used to regenerate the filter had almost no impact on solid particle filtration efficiency but impacted NOx control. Cycling resulted in the formation of very low concentrations of semivolatile nucleation mode particles for some 4WCFS formulations. Overall, 4WCFS show promise for significantly reducing diesel emissions into the atmosphere in a single control device.