8 resultados para Particulate Matter Distribution

em Digital Commons - Michigan Tech


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The particulate matter distribution (PM) trends that exist in catalyzed particulate filters (CPFs) after loading, passive oxidation, active regeneration, and post loading conditions are not clearly understood. These data are required to optimize the operation of CPFs, prevent damage to the CPFs caused by non-uniform distributions, and develop accurate CPF models. To develop an understanding of PM distribution trends, multiple tests were conducted and the PM distribution was measured in three dimensions using a terahertz wave scanner. The results of this work indicate that loading, passive oxidation, active regeneration, and post loading can all cause non-uniform PM distributions. The density of the PM in the substrate after loading and the amount of PM that is oxidized during passive oxidations and active regenerations affect the uniformity of the distribution. Post loading that occurs after active regenerations result in distributions that are less uniform than post loading that occurs after passive oxidations.

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Active regeneration experiments were carried out on a production 2007 Cummins 8.9L ISL engine and associated DOC and CPF aftertreatment system. The effects of SME biodiesel blends were investigated in this study in order to determine the PM oxidation kinetics associated with active regeneration, and to determine the effect of biodiesel on them. The experimental data from this study will also be used to calibrate the MTU-1D CPF model. Accurately predicting the PM mass retained in the CPF and the oxidation characteristics will provide the basis for computation in the ECU that will minimize the fuel penalty associated with active regeneration. An active regeneration test procedure was developed based on previous experimentation at MTU. During each experiment, the PM mass in the CPF is determined by weighing the filter at various phases. In addition, DOC and CPF pressure drop, particle size distribution, gaseous emissions, temperature, and PM concentration data are collected and recorded throughout each experiment. The experiments covered a range of CPF inlet temperatures using ULSD, B10, and B20 blends of biodiesel. The majority of the tests were performed at CPF PM loading of 2.2 g/L with in-cylinder dosing, although 4.1 g/L and a post-turbo dosing injector were also used. The PM oxidation characteristics at different test conditions were studied in order to determine the effects of biodiesel on PM oxidation during active regeneration. A PM reaction rate calculation method was developed to determine the global activation energy and the corresponding pre-exponential factor for all test fuels. The changing sum of the total flow resistance of the wall, cake, and channels was also determined as part of the data analysis process in order to check on the integrity of the data and to correct input data to be consistent with the expected trends of the resistance based on the engine conditions used in the test procedure. It was determined that increasing the percent biodiesel content in the test fuel tends to increase the PM reaction rate and the regeneration efficiency of fuel dosing, i.e., at a constant CPF inlet temperature, B20 test fuel resulted in the highest PM reaction rate and regeneration efficiency of fuel dosing. Increasing the CPF inlet temperature also increases PM reaction rate and regeneration efficiency of fuel dosing. Performing active regeneration with B20 as opposed to ULSD allows for a lower CPF temperature to be used to reach the same level of regeneration efficiency, or it allows for a shorter regeneration time at a constant CPF temperature, resulting in decreased fuel consumption for the engine during active regeneration in either scenario.

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Back-pressure on a diesel engine equipped with an aftertreatment system is a function of the pressure drop across the individual components of the aftertreatment system, typically, a diesel oxidation catalyst (DOC), catalyzed particulate filter (CPF) and selective catalytic reduction (SCR) catalyst. Pressure drop across the CPF is a function of the mass flow rate and the temperature of the exhaust flowing through it as well as the mass of particulate matter (PM) retained in the substrate wall and the cake layer that forms on the substrate wall. Therefore, in order to control the back-pressure on the engine at low levels and to minimize the fuel consumption, it is important to control the PM mass retained in the CPF. Chemical reactions involving the oxidation of PM under passive oxidation and active regeneration conditions can be utilized with computer numerical models in the engine control unit (ECU) to control the pressure drop across the CPF. Hence, understanding and predicting the filtration and oxidation of PM in the CPF and the effect of these processes on the pressure drop across the CPF are necessary for developing control strategies for the aftertreatment system to reduce back-pressure on the engine and in turn fuel consumption particularly from active regeneration. Numerical modeling of CPF's has been proven to reduce development time and the cost of aftertreatment systems used in production as well as to facilitate understanding of the internal processes occurring during different operating conditions that the particulate filter is subjected to. A numerical model of the CPF was developed in this research work which was calibrated to data from passive oxidation and active regeneration experiments in order to determine the kinetic parameters for oxidation of PM and nitrogen oxides along with the model filtration parameters. The research results include the comparison between the model and the experimental data for pressure drop, PM mass retained, filtration efficiencies, CPF outlet gas temperatures and species (NO2) concentrations out of the CPF. Comparisons of PM oxidation reaction rates obtained from the model calibration to the data from the experiments for ULSD, 10 and 20% biodiesel-blended fuels are presented.

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The emissions, filtration and oxidation characteristics of a diesel oxidation catalyst (DOC) and a catalyzed particulate filter (CPF) in a Johnson Matthey catalyzed continuously regenerating trap (CCRT ®) were studied by using computational models. Experimental data needed to calibrate the models were obtained by characterization experiments with raw exhaust sampling from a Cummins ISM 2002 engine with variable geometry turbocharging (VGT) and programmed exhaust gas recirculation (EGR). The experiments were performed at 20, 40, 60 and 75% of full load (1120 Nm) at rated speed (2100 rpm), with and without the DOC upstream of the CPF. This was done to study the effect of temperature and CPF-inlet NO2 concentrations on particulate matter oxidation in the CCRT ®. A previously developed computational model was used to determine the kinetic parameters describing the oxidation characteristics of HCs, CO and NO in the DOC and the pressure drop across it. The model was calibrated at five temperatures in the range of 280 – 465° C, and exhaust volumetric flow rates of 0.447 – 0.843 act-m3/sec. The downstream HCs, CO and NO concentrations were predicted by the DOC model to within ±3 ppm. The HCs and CO oxidation kinetics in the temperature range of 280 - 465°C and an exhaust volumetric flow rate of 0.447 - 0.843 act-m3/sec can be represented by one ’apparent’ activation energy and pre-exponential factor. The NO oxidation kinetics in the same temperature and exhaust flow rate range can be represented by ’apparent’ activation energies and pre-exponential factors in two regimes. The DOC pressure drop was always predicted within 0.5 kPa by the model. The MTU 1-D 2-layer CPF model was enhanced in several ways to better model the performance of the CCRT ®. A model to simulate the oxidation of particulate inside the filter wall was developed. A particulate cake layer filtration model which describes particle filtration in terms of more fundamental parameters was developed and coupled to the wall oxidation model. To better model the particulate oxidation kinetics, a model to take into account the NO2 produced in the washcoat of the CPF was developed. The overall 1-D 2-layer model can be used to predict the pressure drop of the exhaust gas across the filter, the evolution of particulate mass inside the filter, the particulate mass oxidized, the filtration efficiency and the particle number distribution downstream of the CPF. The model was used to better understand the internal performance of the CCRT®, by determining the components of the total pressure drop across the filter, by classifying the total particulate matter in layer I, layer II, the filter wall, and by the means of oxidation i.e. by O2, NO2 entering the filter and by NO2 being produced in the filter. The CPF model was calibrated at four temperatures in the range of 280 – 465 °C, and exhaust volumetric flow rates of 0.447 – 0.843 act-m3/sec, in CPF-only and CCRT ® (DOC+CPF) configurations. The clean filter wall permeability was determined to be 2.00E-13 m2, which is in agreement with values in the literature for cordierite filters. The particulate packing density in the filter wall had values between 2.92 kg/m3 - 3.95 kg/m3 for all the loads. The mean pore size of the catalyst loaded filter wall was found to be 11.0 µm. The particulate cake packing densities and permeabilities, ranged from 131 kg/m3 - 134 kg/m3, and 0.42E-14 m2 and 2.00E-14 m2 respectively, and are in agreement with the Peclet number correlations in the literature. Particulate cake layer porosities determined from the particulate cake layer filtration model ranged between 0.841 and 0.814 and decreased with load, which is about 0.1 lower than experimental and more complex discrete particle simulations in the literature. The thickness of layer I was kept constant at 20 µm. The model kinetics in the CPF-only and CCRT ® configurations, showed that no ’catalyst effect’ with O2 was present. The kinetic parameters for the NO2-assisted oxidation of particulate in the CPF were determined from the simulation of transient temperature programmed oxidation data in the literature. It was determined that the thermal and NO2 kinetic parameters do not change with temperature, exhaust flow rate or NO2 concentrations. However, different kinetic parameters are used for particulate oxidation in the wall and on the wall. Model results showed that oxidation of particulate in the pores of the filter wall can cause disproportionate decreases in the filter pressure drop with respect to particulate mass. The wall oxidation model along with the particulate cake filtration model were developed to model the sudden and rapid decreases in pressure drop across the CPF. The particulate cake and wall filtration models result in higher particulate filtration efficiencies than with just the wall filtration model, with overall filtration efficiencies of 98-99% being predicted by the model. The pre-exponential factors for oxidation by NO2 did not change with temperature or NO2 concentrations because of the NO2 wall production model. In both CPF-only and CCRT ® configurations, the model showed NO2 and layer I to be the dominant means and dominant physical location of particulate oxidation respectively. However, at temperatures of 280 °C, NO2 is not a significant oxidizer of particulate matter, which is in agreement with studies in the literature. The model showed that 8.6 and 81.6% of the CPF-inlet particulate matter was oxidized after 5 hours at 20 and 75% load in CCRT® configuration. In CPF-only configuration at the same loads, the model showed that after 5 hours, 4.4 and 64.8% of the inlet particulate matter was oxidized. The increase in NO2 concentrations across the DOC contributes significantly to the oxidation of particulate in the CPF and is supplemented by the oxidation of NO to NO2 by the catalyst in the CPF, which increases the particulate oxidation rates. From the model, it was determined that the catalyst in the CPF modeslty increases the particulate oxidation rates in the range of 4.5 – 8.3% in the CCRT® configuration. Hence, the catalyst loading in the CPF of the CCRT® could possibly be reduced without significantly decreasing particulate oxidation rates leading to catalyst cost savings and better engine performance due to lower exhaust backpressures.

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Due to their high thermal efficiency, diesel engines have excellent fuel economy and have been widely used as a power source for many vehicles. Diesel engines emit less greenhouse gases (carbon dioxide) compared with gasoline engines. However, diesel engines emit large amounts of particulate matter (PM) which can imperil human health. The best way to reduce the particulate matter is by using the Diesel Particulate Filter (DPF) system which consists of a wall-flow monolith which can trap particulates, and the DPF can be periodically regenerated to remove the collected particulates. The estimation of the PM mass accumulated in the DPF and total pressure drop across the filter are very important in order to determine when to carry out the active regeneration for the DPF. In this project, by developing a filtration model and a pressure drop model, we can estimate the PM mass and the total pressure drop, then, these two models can be linked with a regeneration model which has been developed previously to predict when to regenerate the filter. There results of this project were: 1 Reproduce a filtration model and simulate the processes of filtration. By studying the deep bed filtration and cake filtration, stages and quantity of mass accumulated in the DPF can be estimated. It was found that the filtration efficiency increases faster during the deep-bed filtration than that during the cake filtration. A “unit collector” theory was used in our filtration model which can explain the mechanism of the filtration very well. 2 Perform a parametric study on the pressure drop model for changes in engine exhaust flow rate, deposit layer thickness, and inlet temperature. It was found that there are five primary variables impacting the pressure drop in the DPF which are temperature gradient along the channel, deposit layer thickness, deposit layer permeability, wall thickness, and wall permeability. 3 Link the filtration model and the pressure drop model with the regeneration model to determine the time to carry out the regeneration of the DPF. It was found that the regeneration should be initiated when the cake layer is at a certain thickness, since a cake layer with either too big or too small an amount of particulates will need more thermal energy to reach a higher regeneration efficiency. 4 Formulate diesel particulate trap regeneration strategies for real world driving conditions to find out the best desirable conditions for DPF regeneration. It was found that the regeneration should be initiated when the vehicle’s speed is high and during which there should not be any stops from the vehicle. Moreover, the regeneration duration is about 120 seconds and the inlet temperature for the regeneration is 710K.

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A diesel oxidation catalyst (DOC) with a catalyzed diesel particulate filter (CPF) is an effective exhaust aftertreatment device that reduces particulate emissions from diesel engines, and properly designed DOC-CPF systems provide passive regeneration of the filter by the oxidation of PM via thermal and NO2/temperature-assisted means under various vehicle duty cycles. However, controlling the backpressure on engines caused by the addition of the CPF to the exhaust system requires a good understanding of the filtration and oxidation processes taking place inside the filter as the deposition and oxidation of solid particulate matter (PM) change as functions of loading time. In order to understand the solid PM loading characteristics in the CPF, an experimental and modeling study was conducted using emissions data measured from the exhaust of a John Deere 6.8 liter, turbocharged and after-cooled engine with a low-pressure loop EGR system and a DOC-CPF system (or a CCRT® - Catalyzed Continuously Regenerating Trap®, as named by Johnson Matthey) in the exhaust system. A series of experiments were conducted to evaluate the performance of the DOC-only, CPF-only and DOC-CPF configurations at two engine speeds (2200 and 1650 rpm) and various loads on the engine ranging from 5 to 100% of maximum torque at both speeds. Pressure drop across the DOC and CPF, mass deposited in the CPF at the end of loading, upstream and downstream gaseous and particulate emissions, and particle size distributions were measured at different times during the experiments to characterize the pressure drop and filtration efficiency of the DOCCPF system as functions of loading time. Pressure drop characteristics measured experimentally across the DOC-CPF system showed a distinct deep-bed filtration region characterized by a non-linear pressure drop rise, followed by a transition region, and then by a cake-filtration region with steadily increasing pressure drop with loading time at engine load cases with CPF inlet temperatures less than 325 °C. At the engine load cases with CPF inlet temperatures greater than 360 °C, the deep-bed filtration region had a steep rise in pressure drop followed by a decrease in pressure drop (due to wall PM oxidation) in the cake filtration region. Filtration efficiencies observed during PM cake filtration were greater than 90% in all engine load cases. Two computer models, i.e., the MTU 1-D DOC model and the MTU 1-D 2-layer CPF model were developed and/or improved from existing models as part of this research and calibrated using the data obtained from these experiments. The 1-D DOC model employs a three-way catalytic reaction scheme for CO, HC and NO oxidation, and is used to predict CO, HC, NO and NO2 concentrations downstream of the DOC. Calibration results from the 1-D DOC model to experimental data at 2200 and 1650 rpm are presented. The 1-D 2-layer CPF model uses a ‘2-filters in series approach’ for filtration, PM deposition and oxidation in the PM cake and substrate wall via thermal (O2) and NO2/temperature-assisted mechanisms, and production of NO2 as the exhaust gas mixture passes through the CPF catalyst washcoat. Calibration results from the 1-D 2-layer CPF model to experimental data at 2200 rpm are presented. Comparisons of filtration and oxidation behavior of the CPF at sample load-cases in both configurations are also presented. The input parameters and selected results are also compared with a similar research work with an earlier version of the CCRT®, to compare and explain differences in the fundamental behavior of the CCRT® used in these two research studies. An analysis of the results from the calibrated CPF model suggests that pressure drop across the CPF depends mainly on PM loading and oxidation in the substrate wall, and also that the substrate wall initiates PM filtration and helps in forming a PM cake layer on the wall. After formation of the PM cake layer of about 1-2 µm on the wall, the PM cake becomes the primary filter and performs 98-99% of PM filtration. In all load cases, most of PM mass deposited was in the PM cake layer, and PM oxidation in the PM cake layer accounted for 95-99% of total PM mass oxidized during loading. Overall PM oxidation efficiency of the DOC-CPF device increased with increasing CPF inlet temperatures and NO2 flow rates, and was higher in the CCRT® configuration compared to the CPF-only configuration due to higher CPF inlet NO2 concentrations. Filtration efficiencies greater than 90% were observed within 90-100 minutes of loading time (starting with a clean filter) in all load cases, due to the fact that the PM cake on the substrate wall forms a very efficient filter. A good strategy for maintaining high filtration efficiency and low pressure drop of the device while performing active regeneration would be to clean the PM cake filter partially (i.e., by retaining a cake layer of 1-2 µm thickness on the substrate wall) and to completely oxidize the PM deposited in the substrate wall. The data presented support this strategy.

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A 2007 Cummins ISL 8.9L direct-injection common rail diesel engine rated at 272 kW (365 hp) and 317 kW (425 hp) was used to load the filter to 2.2 g/L and passively oxidize particulate matter (PM) within an aftertreatment system consisting of a diesel oxidation catalyst (DOC) and catalyzed particulate filter (CPF). The tests conducted with the engine rated at 365 hp used a 2007 DOC and CPF. The tests conducted with the engine rated at 425 hp used a 2010 DOC and 2007 CPF. Understanding the passive NO2 oxidation kinetics of PM within the CPF allows for reducing the frequency of active regenerations (hydrocarbon injection) and the associated fuel penalties. Modeling the passive oxidation of accumulated PM in the CPF will lead to creating accurate state estimation strategies. The MTU 1-D CPF model will be used to simulate data collected from this study to examine differences in the PM oxidation kinetics when soy methyl ester (SME) biodiesel is used as the source of fuel for the engine, and when the engine is operated at a higher power rating. A test procedure developed by Hutton et al. [1, 2] was modified to improve the ability to model the experimental data and provide additional insight into passively oxidized PM in a partially regenerated CPF. A test procedure was developed to allow PM oxidation rates by NO2 to be determined from engine test cell data. An experimental matrix consisting of CPF inlet temperatures from 250 to 450 °C with varying NOX/PM from 25 to 583and NO2/PM ratios from 5 to 240 was used. SME biodiesel was volumetrically blended with ULSD in 10% (B10) and 20% (B20) portions. This blended fuel was then used to evaluate the effect of biodiesel on passive oxidation rates. Four tests were performed with B10 and four tests with B20. Gathering data to determine the effect of fuel type (ULSD and biodiesel blends) on PM oxidation is the primary goal. The engine used for this testing was then configured to a higher power rating and one of the tests planned was performed. Additional testing is scheduled to take place with ULSD fuel to determine the affect the engine rating has on the PM oxidation. The experimental reaction rates during passive oxidation varied based upon the average CPF temperature, NO2 concentrations, and the NOX/PM ratios for each engine rating and with all fuels. The data analysis requires a high fidelity model that includes NO2 and thermal oxidation mechanisms and back diffusion to determine the details of the PM oxidation process.

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Particulate matter (PM) emissions standards set by the US Environmental Protection Agency (EPA) have become increasingly stringent over the years. The EPA regulation for PM in heavy duty diesel engines has been reduced to 0.01 g/bhp-hr for the year 2010. Heavy duty diesel engines make use of an aftertreatment filtration device, the Diesel Particulate Filter (DPF). DPFs are highly efficient in filtering PM (known as soot) and are an integral part of 2010 heavy duty diesel aftertreatment system. PM is accumulated in the DPF as the exhaust gas flows through it. This PM needs to be removed by oxidation periodically for the efficient functioning of the filter. This oxidation process is also known as regeneration. There are 2 types of regeneration processes, namely active regeneration (oxidation of PM by external means) and passive oxidation (oxidation of PM by internal means). Active regeneration occurs typically in high temperature regions, about 500 - 600 °C, which is much higher than normal diesel exhaust temperatures. Thus, the exhaust temperature has to be raised with the help of external devices like a Diesel Oxidation Catalyst (DOC) or a fuel burner. The O2 oxidizes PM producing CO2 as oxidation product. In passive oxidation, one way of regeneration is by the use of NO2. NO2 oxidizes the PM producing NO and CO2 as oxidation products. The passive oxidation process occurs at lower temperatures (200 - 400 °C) in comparison to the active regeneration temperatures. Generally, DPF substrate walls are washcoated with catalyst material to speed up the rate of PM oxidation. The catalyst washcoat is observed to increase the rate of PM oxidation. The goal of this research is to develop a simple mathematical model to simulate the PM depletion during the active regeneration process in a DPF (catalyzed and non-catalyzed). A simple, zero-dimensional kinetic model was developed in MATLAB. Experimental data required for calibration was obtained by active regeneration experiments performed on PM loaded mini DPFs in an automated flow reactor. The DPFs were loaded with PM from the exhaust of a commercial heavy duty diesel engine. The model was calibrated to the data obtained from active regeneration experiments. Numerical gradient based optimization techniques were used to estimate the kinetic parameters of the model.