Diesel Particulate Filter Regeneration Research Articles

Investigation of the Impact of Regeneration Temperature and Methanol Substitution Rate on the Active Regeneration of Diesel Particulate Filter in a Diesel-Methanol Dual-Fuel Engine

Methanol (CH3OH), a sustainable fuel derived from many renewable resources, simultaneously reduces nitrogen oxides (NOx) and particulate matter (PM) in diesel-methanol dual-fuel engines. This study systematically investigated the effects of regeneration temperature and methanol substitution rate (MSR) on the performance of diesel oxidation catalyst (DOC), diesel particulate filter (DPF), and the temperature characteristics of DPF substrate during active regeneration. The experimental results show that the DOC catalytic oxidation of unburned CH3OH has a conversion rate of more than 97.5% across various MSR. DPF inlet temperature rose faster with higher MSR. Elevated regeneration temperature reduced effective regeneration times and diesel equivalent consumption. Within active regeneration conditions with MSR increases, both effective regeneration times and diesel equivalent consumption initially decreased and then increased as the MSR rose. At MSR=30%, the duration of effective regeneration times during DPF active regeneration was minimized, and diesel equivalent consumption at MSR=30% experienced an improvement of 22.52% compared to MSR=0%. The highest DPF substrate temperatures across various MSR levels are consistently observed at T6 position within the DPF. This study can provide a theoretical basis for the active regeneration of DPF in methanol-diesel dual-fuel mode.

Effect soluble organic fraction mass fraction on emission characteristics of carbon black

AbstractAccording to China's latest emission regulations for the year 2021, diesel vehicles are required to be equipped with a diesel particulate filter (DPF) in accordance with emission standards. To comprehensively understand the regeneration and emission performance of the DPF, an externally heated regeneration performance test bench was established. This study aims to investigate the influence of the soluble organic fraction (SOF) and types of carbon black on particle emissions from the outlet of the DPF. The experimental results indicate that both SOF and carbon black structure can affect DPF regeneration. When the SOF mass fraction increases to 20%, SOF plays a dominant role. The regeneration efficiency of Printex‐U and FW200 carbon black is 62.4% and 60.6%, respectively, with total mass concentrations of 21.8 and 14.9 mg/m3 at the DPF outlet. Compared to conditions without SOF, the regeneration efficiency and total mass concentration at the DPF outlet increase by 1.3 times and 6.6 times for Printex‐U carbon black, and 1.8 times and 440 times for FW200 carbon black, respectively. Additionally, when SOF mass fraction is 0%, the highest proportion of the average particle diameter for both Printex‐U and FW200 carbon black is in the [10, 20] nm range, at 20% and 95%, respectively. When the SOF mass fraction is increased to 20%, the proportions of the average particle diameter for both types of carbon black in the [10, 20] nm range rise to above 99%. This study provides a relevant experimental foundation for the emission control of DPF.

Soot particles formed by n-heptane and n-heptane/oxymethylene ether-3 in an inverse diffusion flame: A comparative analysis of chemical features

Oxymethylene ether-3 (OME3) is a promising synthetic e-fuel and alternative fuel for diesel engines. In contrast to diesel fuel, the use of OME3 leads to a distinct combustion process in which soot particles are generated, which leads to changes in the chemical properties of these particles. These chemical properties are intricately connected to both the concentration and availability of potential radical sites, which, in turn, exert a substantial influence on soot oxidation during diesel particulate filter (DPF) regeneration. Hence, it is crucial to investigate the chemical features of soot samples. Nevertheless, a thorough investigation into the chemical features of n-heptane/OME3 soot samples has not been fully understood. Here, X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FT-IR), elemental analyser, and thermogravimetric analysis (TGA) were used to examine the impact of blending OME3 on chemical features of soot particles at various flame heights of an inverse n-heptane-OME3 flame. XPS results from C1s and O1s peaks showed that OME3 incorporation enhanced the concentrations of C = O, C–O, and O = C–O groups, especially C = O groups, with the percentage increase ranging from 11.93 % to 49.74 %. Similarly, the content of aliphatic C − H groups, along with O and H, increased with higher levels of OME3 blending. Moreover, it was discovered that blending OME3 altered the spatial distribution of hybridisation orbitals of carbon atoms, leading to a decrease in the sp2/sp3 ratio by as much as 40 % with the increase in the OME3 blending ratio. The alteration in these chemical properties due to the addition of OME3 enhanced the oxidative reactivity of soot particles, as manifested by up to a 15 % reduction in the measured activation energy. These findings are useful to optimise control strategies of DPF regeneration with the more widespread use of e-fuel.

Improvement and prediction of particles emission from diesel particulate filter based on an integrated artificial neural network

Diesel Particulate Filter (DPF) stands out as a highly effective device for mitigating emissions in engines. To enhance DPF regeneration performance, the numerical model and the GA-BP neural network model are developed, which delves into the impacts of velocity, temperature, oxygen mass fraction, and particles size on particulate conversion. The results show that conversion rate of carbon particles can be elevated by increasing the oxygen mass fraction and inlet velocity. Specifically, the conversion rate demonstrates a remarkable improvement of 37.41% at Tin = 600 K, de = 5 μm, Vin = 10 m/s, and mO2 increased from 0.01 to 0.04. Additionally, conversion rates are increased as the size of the carbon particles gradually reduced. Besides, a GA-BP neural network is deployed to analyze and predict the numerical results of 1818 sets of DPFs under different operating conditions. From the analysis and prediction of 132 data sets, and it is discerned that a high state of contamination transformation can be achieved at Tin = 525 K, de = 5 μm, Vin = 12 m/s and mO2 = 0.04. This demonstrates the significance of judiciously selecting boundary conditions for realizing effective regenerative emission reduction.

Towards zero pollution vehicles by advanced fuels and exhaust aftertreatment technologies

Vehicular emissions deteriorate air quality in urban areas notably. The aim of this study was to conduct an in-depth characterization of gaseous and particle emissions, and their potential to form secondary aerosol emissions, of the cars meeting the most recent emission Euro 6d standards, and to investigate the impact of fuel as well as engine and aftertreatment technologies on pollutants at warm and cold ambient temperatures. Studied vehicles were a diesel car with a diesel particulate filter (DPF), two gasoline cars (with and without a gasoline particulate filter (GPF)), and a car using compressed natural gas (CNG). The impact of fuel aromatic content was examined for the diesel car and the gasoline car without the GPF. The results showed that the utilization of exhaust particulate filter was important both in diesel and gasoline cars. The gasoline car without the GPF emitted relatively high concentrations of particles compared to the other technologies but the implementation of the GPF decreased particle emissions, and the potential to form secondary aerosols in atmospheric processes. The diesel car equipped with the DPF emitted low particle number concentrations except during the DPF regeneration events. Aromatic-free gasoline and diesel fuel efficiently reduced exhaust particles. Since the renewal of vehicle fleet is a relatively slow process, changing the fuel composition can be seen as a faster way to affect traffic emissions.

Experimental effects of ash (ZnO) and catalyst (CeO[formula omitted]) on DPF regeneration performance and emission characteristics

The regeneration characteristics of a diesel particulate filter (DPF) are studied on a regeneration test bench, with a focus on the effects of ash and catalyst, including the effects of ZnO and CeO2 on the regeneration performance and emission characteristics of the DPF. The results indicate that the addition of ZnO and CeO2 can easily lead to local high temperatures during the regeneration process of the DPF, with the highest peak temperature appearing in a 1:3 ratio for both ZnO and CeO2, leading to a significant increase in CO2. Compared with ZnO, CeO2 can advance the DPF rapid regeneration period by about 300 s. When the ratio of PU: CeO2 is 1:5, the total particulate matter emitted is reduced to the lowest level, but it will significantly increase the emission of nuclear model particles, especially particles below 23 nm. Under the same mixing ratio, an increase in carbon loading can enhance the oxidation ability of ZnO towards carbon black, but the difference between the number of particles emitted during DPF regeneration and regeneration efficiency will gradually decrease.

Nonlinear model predictive control(NMPC) of diesel oxidation catalyst (DOC) outlet temperature for active regeneration of diesel particulate filter (DPF) in diesel engine

To meet the active regeneration requirements of the diesel particulate filter (DPF), the outlet temperature of the diesel oxidation catalyst (DOC) must be maintained within the range of 585 °C–615 °C. Firstly, this paper explores the DOC system using a set of partial differential equations that describe the coupled flow and heat transfer of both the gas phase and solid phase carriers. Subsequently, the DOC model is significantly simplified, and the equations are solved based on their characteristics. Secondly, a Luenberger observer is designed, and the appropriate range of values for the observer gain is calculated. By minimizing the cost function and adhering to constraints within a finite prediction horizon, the optimal sequence for injecting hydrocarbon(HC) is determined. Thirdly, in this study, a Worldwide Harmonized Transient Cycle test is conducted on the engine, following the China VI emission standard. The computational results demonstrate that the mean absolute errors of the DOC outlet temperatures obtained from the model prediction and the observer are 0.535 °C and 1.994 °C, respectively. Finally, a nonlinear model predictive control is implemented to ensure that the DOC outlet temperature can be maintained between 585 °C and 615 °C.

Research on the method of diesel particulate filters carbon load recognition based on deep learning

Because the carbon load inside a diesel particulate filters (DPF) affects the DPF regeneration, and the carbon load recognition is significant for the particulate matter (PM) emission control. It is necessary to investigate an on-board DPF carbon load recognition method because the carbon load cannot be directly measured by sensors. Aiming to build a DPF carbon load prediction model adopting the deep learning method, this paper proposes a DPF carbon load identification model based on different experimental parameters using a layered one dimension convolutional neural network (1D-CNN) method. To improve data validity, this paper adopts two data-processing methods. The data pre-processing adopts data splicing method to complete the construction of the original sample set, and the data after-processing uses wavelet packet transform method to establish the feature sample sets. The model adopts the optimal feature dataset constructed by three input parameters, i.e., temperature difference, pressure difference, and exhaust mass flow, and has both high training accuracy and test accuracy above 90 %. The pressure difference is the most important influencing input parameter, and the three-parameter sample set (ΔT + ΔP + Q) has great recognition accuracy and good model stability with the high training accuracy and test accuracy as well as less iteration.

Effect of non-thermal plasma injection flow rate on diesel particulate filter regeneration at room temperature

Effect of non-thermal plasma injection flow rate on diesel particulate filter regeneration at room temperature

Investigation of the physicochemical properties of soot subjected to non-catalytic and CeO2-catalytic aging under sequential aerobic and anaerobic exhaust-like conditions simulating the transition from engine operation to cessation

Understanding the physicochemical properties of aged soot particles is crucial for enhancing diesel particulate filter (DPF) regeneration strategies. This study examines the physicochemical properties of such soot subjected to both non-catalytic and CeO2-catalytic aging, utilizing a fixed bed test bench where soot samples are aerobically aged at 300–500 °C for 30–90 min before being cooled to ambient temperature under anaerobic conditions. The results indicate that sequential aging at 300–400 °C has minimal impact on soot oxidation activity, with a slight reduction in ignition temperature compared to nascent soot. Concurrently, there is a notable decrease in soot agglomeration, resulting in reduced macropore sizes ranging from 100 nm to 210 nm. The effects of non-catalytic and catalytic aging on soot oxidation activity diverge significantly at 500 °C. The crystallite arrangement in the soot particles takes precedence over oxidation activity, despite the formation of numerous pores post aging above 400 °C. Graphitization in non-catalytically aged soot increases, whereas it decreases following catalytic sequential aging. Post sequential aging at temperatures ranging from 300 to 500 °C, a noticeable shift occurs in soot particles, characterized by the depletion of CO functional groups and concurrent emergence of CO functional groups. Moreover, the presence of catalysts during this aging process markedly enhances the reduction of CO functional groups.

Experimental study of CeO2 after hydrothermal aging on emission characteristics of carbon black oxidation process

The CeO2 catalyst is commonly utilized in diesel particulate filter (DPF) to promote soot regeneration. It is necessary to give a particular attention to the performance of hydrothermal aging and the effect on DPF regeneration characteristics. Based on the fixed-bed test bench, the gas and particle emission characteristics of carbon black (PU) oxidation following hydrothermal aging and sieving treatment of CeO2 are investigated under a 3% water concentration condition. CeO2 is subjected to characterization and analysis combined with X-ray Photoelectron Spectroscopy (XPS), Electron Spin Resonance Spectroscopy (ESR), X-ray Powder Diffraction (XRD), and Scanning Electron Microscopy (SEM). The results indicate that the addition of fresh CeO2 proves beneficial in improving the oxidation efficiency (η) of PU, reducing CO emission and the total average particle number (PN). Meanwhile, CO2 emission rapidly increases. After hydrothermal aging, the average catalyst size and agglomeration degree of CeO2 increase, resulting in an increase in lattice defects and bulk oxygen vacancies (VO-b). The reduction of surface oxygen vacancies (VO-s) plays a dominant role in the catalytic oxidation process of PU, leading to a decrease in η and CO2 emission, while CO increase; And the contact mode between CeO2 and PU, as well as alterations in the microstructure of CeO2, consequently contributing to hindering particle movement and reducing total PN. Furthermore, the sieving treatment of catalyst increases particle emission, but significantly promotes the η and reduces harmful gas CO. This research establishes a theoretical and experimental foundation for enhancing the hydrothermal stability of catalysts and controlling particle emission at the DPF outlet.

Experimental Study on a Fire Caused by Diesel Particulate Filter Regeneration

In this study, a vehicle fire caused by diesel particulate filter (DPF) regeneration in a truck was investigated and analyzed. A DPF is a filter that collects soot from the exhaust gas; when certain conditions are met, the soot collected in the DPF is burned by the high-temperature exhaust gas. This process is referred to as regeneration. During DPF regeneration, the high-temperature exhaust gas is ejected and combustibles around the exhaust outlet under the vehicle may ignite. Herein, we analyzed a case of fire that occurred in an underground parking lot in 2022. The vehicle was parked for loading, and the fire broke out approximately 6 min later. During the field investigation, traces of combustion were observed in the paper boxes stacked around the truck’s exhaust port. Thus, we conducted a DPF regeneration experiment using a vehicle similar to that which caught fire. The experimental results confirmed that the surrounding combustibles can be ignited by the high-temperature heat generated during DPF regeneration. Further analysis indicated the necessity of being aware of the risk of fire owing to DPF regeneration when vehicles are parked or stopped and combustible materials are present around the exhaust outlet.

Modeling of diesel particulate filter temperature dynamics during exotherm using neural networks

Diesel Particulate Filter (DPF) in the diesel engine exhaust stream needs frequent regeneration (exotherm) to remove captured particulate matter (PM, or soot) without damaging to the porous DPF structure by controlling the peak temperatures and temperature gradients across the DPF. In this study, temperature distribution in a DPF is measured at 42 strategic locations in the test DPF under various regeneration conditions of exhaust flow rates, regeneration temperatures and soot loads. Then a data-based model with feed-forward neural network architecture is designed to model the thermal gradients and temperature dynamics of the DPF during the regeneration process. The neural network feature vector selection, network architecture, hyperparameter calibration process, measured data preprocessing, and experimental data acquisition procedure are evaluated. Over 7,400 experimental data points at various regeneration temperatures, flow rates and soot loads are used in training and validating the neural network model. It is found that the neural network model can accurately predict the 42 DPF bed temperatures simultaneously at different locations, and the time series analysis of both model-predicted and experimentally measured temperatures shows a good correlation. This indicates that the currently developed neural network model can provide spatial distribution of temperature in the DPF, and comprehend the nonlinearity of the temperature dynamics due to DPF soot load at exothermic conditions. These results demonstrate that the data-based model has capability in predicting thermal gradients within a DPF, aiding in determining a safer DPF regeneration strategy, onboard diagnostics and DPF development.

Multi-objective optimization study of hydrothermal aging on NOx-assisted soot catalytic combustion and secondary pollution emission in regeneration of CeO2 catalytic diesel particulate filter

The present study aimed to explore the effect of hydrothermal aging on the heterogeneous catalytic combustion process of soot in CeO2 catalytic diesel particular filter and the formation of secondary pollutants (N2O and CO).The present study was based on a fixed-bed experimental bench for NOx-assisted soot catalytic oxidation in CeO2-CDPF with different soot loading and catalyst coating amounts. A non-linear regression surrogate model and a multi-objective optimization decision approach were used to analyze the trade-off relationship between the design variables and the optimization objectives. The results showed that lower levels of soot loading (2.5 g/L), CeO2 catalyst coating amount (2.5 g/L) and higher NOx concentration (1000 ppm) in fresh catalysts were favorable for improving the performance of soot-assisted catalytic combustion and minimizing the formation of N2O and CO. However, it was observed that higher levels of catalyst coating amount (10 g/L) resulted in better soot catalytic combustion performance with lower N2O and CO emissions. Global sensitivity analysis showed a positive correlation between N2O and CO peak concentrations and peak temperatures with soot loading, but a negative correlation with catalyst loading. Over time, hydrothermal aging of CDPF caused the inhibitory effect of CeO2 catalyst on N2O to shift from negative to positive correlation, while also decreasing the synergistic performance of NOx in soot catalytic combustion.

Thermal management strategy for active regeneration of diesel particulate filter

The method of diesel oxidation catalyst (DOC) assistance is an effective way to achieve active regeneration of diesel particulate filter (DPF). Therefore, an appropriate DOC inlet temperature is the essential boundary condition for this regeneration process. In this paper, the thermal management measures and a novel strategy based on the requirements of DPF active regeneration have been proposed and studied through experiments. Results show that intake throttling can increase DOC inlet temperature by 45% at high speed and 13% at low speed. However, its effect becomes significant only after the throttle closure exceeds 65%. Near post-injection is a more effective method than intake throttling to increase the DOC inlet temperature, and is suitable for situations where the DOC inlet temperature differs greatly from the target value. Under the premise of economic consideration, the optimal value of near post-injection time is always 20°CA after top dead center (TDC). The near post-injection quantity has a greater effect on DOC inlet temperature than the near post-injection time. However, too large near post-injection quantity can also lead to a sharp deterioration in fuel economy. Meanwhile, a novel thermal management strategy based on engine working zone division is proposed according to the ability of different thermal management measures and the distribution law of original DOC inlet temperature. With this strategy, the DOC inlet temperature in whole engine operating range increases significantly. In steady state, more than 80% of the operating points can reach the target value of 450 ℃. In world harmonized transient cycle (WHTC), the average DOC inlet temperature is also increased by 28.8%.

Experimental study on gas and particle emission characteristics of carbon black oxidation process in the presence of water and catalysts

The study of oxidation characteristics of carbon black particle is the basis to investigate the regeneration process and characteristics of diesel particulate filter (DPF). Based on the fixed-bed test bench, the gas and particle emission characteristics of carbon black oxidation process in the presence of water are investigated under different temperatures, Printex-U (PU) masses, and catalysts. The experimental results show that the rise of temperature and PU mass increases the emissions of CO, CO2 and the total average particle number (PN). The oxidation efficiency (η) increases with temperature, but decreases with PU mass. The addition of catalysts promotes PU oxidation, and reduces CO emission. Due to the influence of particle diffusion, CeO2 has slightly lower efficiency than Pt/Al2O3 in the same ratio (1:1), but it is beneficial to significantly reduce particle emission, especially as the ratio increases (1:5). Water decreases CO and the η in PU oxidation, and the negative impact is gradually reduced after 3 % water concentration; However, the PN significantly increases, and expands the particle size range, particularly at high temperature and adding Pt/Al2O3 (from about 10 nm to 6– 30 nm, and a large number of particles with 30– 100 nm are produced). Additionally, the CO2/CO ratio of carbon black oxidation gradually increases with water concentration. Controlling DPF regeneration needs to strike a balance between the benefits on increasing oxidation efficiency and the potential negatives on particulate and harmful gas emission.

A review of regeneration mechanism and methods for reducing soot emissions from diesel particulate filter in diesel engine.

With the global emphasis on environmental protection and the proposal of the climate goal of "carbon neutrality," countries around the world are calling for reductions in carbon dioxide, nitrogen oxide, and particulate matter pollution. These pollutants have severe impacts on human lives and should be effectively controlled. Engine exhaust is the most serious pollution source, and diesel engine is an important contributor to particulate matter. Diesel particulate filter (DPF) technology has proven to be an effective technology for soot control at the present and in the future. Firstly, the exacerbating effect of particulate matter on human infectious disease viruses is discussed. Then, the latest developments in the influence of key factors on DPF performance are reviewed at different observation scales (wall, channel, and entire filter). In addition, current soot catalytic oxidant schemes are presented in the review, and the significance of catalyst activity and soot oxidation kinetic models are highlighted. Finally, the areas that need further research are determined, which has important guiding significance for future research. Current catalytic technologies are focused on stable materials with high mobility of oxidizing substances and low cost. The challenge of DPF optimization design is to accurately calculate the balance between soot and ash load, DPF regeneration control strategy, and exhaust heat management strategy.

Study on CO emission during DOC assisted DPF regeneration

Diesel particulate filters is the most effective post-treatment device used to reduce diesel exhaust particulate emissions. As the amount of particulate matter captured in the diesel particulate filter continues to increase, the exhaust pressure of the diesel engine gradually increases, thereby affecting the power performance of the diesel engine. Therefore, when the particulate matter capture amount reaches a certain value, the diesel particulate matter filter needs to be regenerated. Regeneration of diesel particulate filters will produce secondary pollution, of which CO is one of the most important secondary pollution. In this paper, the CO generation mechanism and influencing factors in the regeneration process of diesel particulate filters are analyzed. The effects of exhaust pressure and exhaust flow on CO emission during regeneration are measured through experiments. The results show that when the exhaust back pressure is greater than 80kPa, the CO solubility in the exhaust gas increases rapidly, and decreases linearly with the increase of exhaust flow during regeneration. Therefore, in order to reduce the solubility of CO in tail gas during regeneration of diesel particulate filters, the exhaust back pressure shall be less than 80kPa and the exhaust flow shall be as high as possible.

Particulate Matter Load Estimation and Distribution Characteristics of Diesel Particulate Filter

This paper focuses on the offline electric heating regeneration technology of DPF (Diesel Particulate Filter). Based on the actual operating conditions of the airport passenger elevator, the pressure drop changes before and after the offline regeneration of DPF, the passive regeneration process during the vehicle operation, and the capture efficiency of PM and PN after the offline regeneration of DPF are studied. The DPF pressure drop increases with the operation time because of the extremely low efficiency of passive regeneration before offline regeneration, and the initial pressure drop after regeneration is slightly higher than that of the fresh carrier due to the existence of ash. When the exhaust temperature reaches 420°C, the DPF passive regeneration rate is higher than the capture rate, and the DPF pressure drop drops rapidly when the passenger elevator continues to run. The mass fraction of fine particulate matter is more than 0.02μm in the cold start stage, while the mass fraction of fine particulate matter is more than 0.02μm in the hot start stage.

Evolution hydrothermal aging mechanism for Ag/CeO2 catalysts in regeneration of catalytic diesel particulate filter with DFT calculation.

In order to avoid the high cost of existing precious metal catalyst like Pt, Ag/CeO2 was the most promising catalysts for mobile source soot emission control technologies, but there was a clear trade-off between hydrothermal aging resistance and catalytic oxidation performance hindered the application of this catalyst. In order to reveal the hydrothermal aging mechanism of Ag/CeO2 catalysts, the TGA (thermogravimetric analysis) experiments were investigated to reveal the mechanism of Ag modification on catalytic activity of CeO2 catalyst between fresh and hydrothermal aging and were also characterized with the related characterization experiments to in-depth research the lattice morphology and valence changes. The degradation mechanism of Ag/CeO2 catalysts in vapor with high-temperature was also explained and demonstrated based on density functional and molecular thermodynamics theories. The experimental and simulation data showed that the catalytic activity of soot combustion within Ag/CeO2 decreased more significantly after hydrothermal aging than CeO2 due to the less agglomerated, which caused by the decreased in OII/OI and Ce3+/Ce4+ compared with CeO2. As shown in density function theory (DFT) calculation, the decreased surface energy and the increased oxygen vacancy formation energy of the low Mille index surface after Ag modification led to the instability structure and the high catalytic activity. Ag modification also increased the adsorption energy and Gibbs free energy of H2O on the low Miller index surface compared to CeO2, indicating that the desorption temperature of H2O molecules in (1 1 0) and (1 0 0) was higher than (1 1 1) in CeO2 and Ag/CeO2, which led to the migration of (1 1 1) crystal surfaces to (1 1 0) and (1 0 0) in the vapor environment. These conclusions can provide a valuable addition to the regenerative application of Ce-based catalysts in diesel exhaust aftertreatment system the aerial pollution.