Abstract:The effect of hydrocarbon slip from a diesel oxidation catalyst on active regeneration of a diesel particulate filter is investigated by developing a generalized zero-dimensional diesel particulate filter model to predict the wall temperature of the diesel particulate filter and the trapped mass of particulate matter. Exhaust fuel injection methodology is applied to provide a high temperature for regeneration by oxidation in the diesel oxidation catalyst. However, the diesel oxidation catalyst reactions may be… Show more
“…In addition to three common reasons for uncontrolled regeneration, a new reason was proposed in Lee and Rutland's model (Lee and Rutland 2012 ). When the additional fuel needed to be injected into DOC for DPF regeneration, some HC substances in the fuel slightly oxidized.…”
“… Fig. 21 Effects of HC leakage and the mass flow rate on the DPF peak wall temperature when the mass flow rate is reduced to 0.01 kg/s (Lee and Rutland 2012 ) …”
Diesel particulate filter (DPF) is considered as an effective method to control particulate matter (PM) emissions from diesel engines, which is included in the mandatory installation list by more and more national/regional laws and regulations, such as CHINA VI, Euro VI, and EPA Tier3. Due to the limited capacity of DPF to contain PM, the manufacturer introduced a method of treating deposited PM by oxidation, which is called regeneration. This paper comprehensively summarizes the most advanced regeneration technology, including filter structure, new catalyst formula, accurate soot prediction, safe and reliable regeneration strategy, uncontrolled regeneration and its control methods. In addition, due to the change of working conditions in the regeneration process, the additional emissions during regeneration are discussed in this paper. The DPF is not only the aftertreatment device but also can be combined with diesel oxidation catalyst (DOC), selective catalytic reduction (SCR) and exhaust recirculation (EGR). In addition, the impact of DPF modification on the original system of some old models has been reasonably discussed in order to achieve emission targets.
“…In addition to three common reasons for uncontrolled regeneration, a new reason was proposed in Lee and Rutland's model (Lee and Rutland 2012 ). When the additional fuel needed to be injected into DOC for DPF regeneration, some HC substances in the fuel slightly oxidized.…”
“… Fig. 21 Effects of HC leakage and the mass flow rate on the DPF peak wall temperature when the mass flow rate is reduced to 0.01 kg/s (Lee and Rutland 2012 ) …”
Diesel particulate filter (DPF) is considered as an effective method to control particulate matter (PM) emissions from diesel engines, which is included in the mandatory installation list by more and more national/regional laws and regulations, such as CHINA VI, Euro VI, and EPA Tier3. Due to the limited capacity of DPF to contain PM, the manufacturer introduced a method of treating deposited PM by oxidation, which is called regeneration. This paper comprehensively summarizes the most advanced regeneration technology, including filter structure, new catalyst formula, accurate soot prediction, safe and reliable regeneration strategy, uncontrolled regeneration and its control methods. In addition, due to the change of working conditions in the regeneration process, the additional emissions during regeneration are discussed in this paper. The DPF is not only the aftertreatment device but also can be combined with diesel oxidation catalyst (DOC), selective catalytic reduction (SCR) and exhaust recirculation (EGR). In addition, the impact of DPF modification on the original system of some old models has been reasonably discussed in order to achieve emission targets.
“…For instance, excess PM loading and high level of soluble organic fraction (SOF) content in PM may cause uncontrolled regeneration in DPF, which may result in device failure. 2 On the other hand, soot deposits in a gasoline particulate filter (GPF) may be continuously burned out as a result of the higher exhaust gas temperature and lower PM mass concentration, and so a soot cake layer would not build up on the channel surface. Overall filtration efficiency may also vary because the size distributions of the particulates differ.…”
A three-dimensional model is developed for computational fluid dynamics analysis of soot filtration processes in a wall flow–type particulate filter based on an Eulerian–Eulerian numerical approach. The primary objective of this study is to accurately capture the local values of filtration parameters, such as volume porosity, collection efficiency, and soot mass deposited, through isotropically discretized computational grids within the multi-layered porous wall regions. Most commercial computational fluid dynamics codes do not have the ability to generate structured mesh with ordered cell index or allow expressing mathematical recursive operation or handling time array through defined user field functions. For these reasons, it is difficult to utilize the code in situations where complex algorithms and mathematical treatments are required. Therefore, custom-build user subroutines, written with C++ programming language, are developed and integrated with the model to calculate localized soot mass distributions in each layer of porous wall. New recursive and computationally efficient algorithms are developed utilizing the functional attributes of the computational fluid dynamics code and coupled with the modified unit collector mechanism in order to obtain temporal and local filtration efficiency. Simulations enabled quantitative visualization of the detailed filtration processes along the filter wall and channel, including the time evolution of filtration parameters, which is difficult to detect experimentally. The model revealed correlations between wall flow pattern and rearrangement behaviors of filtration parameters and provided insights into the soot cake layer profiles with respect to both the length and the width of the channel.
“…However, this mathematical model depends on many filter materials, exhaust gas properties and insitu physical parameter correlation factors. Hoon et al (Lee and Rutland, 2013) modelled the uncontrolled soot regeneration inside the DPF in the presence of hydrocarbon slip by using a physicsbased 0-D modeling technique to predict the transient thermal response, where the temperature, pressure and species concentration of the exhaust across the DPF is considered. In this case, the model assumes that the soot distribution and exhaust species concentration are uniform, which is impractical and relies on the DPF material, geometric parameters and exhaust gas properties.…”
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.
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