Modeling of diesel particulate filter filtration and regeneration for transient driving schedules

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.

Experimental and modeling study of the filtration and oxidation characteristics of a diesel oxidation catalyst and a catalyzed particulate filter

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.

Study of the effect of biodiesel fuel on passive oxidation in a catalyzed particulate filter

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.

Filtration and oxidation characteristics of a diesel oxidation catalyst and a catalyzed particulate filter : development of a 1-D 2-layer model

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.

IMPACT OF ENGINE CALIBRATION ON PM OXIDATION IN A CATALYZED PARTICULATE FILTER OVER A TRANSIENT CYCLE: A MODELLING STUDY

The combustion strategy in a diesel engine has an impact on the emissions, fuel consumption and the exhaust temperatures. The PM mass retained in the CPF is a function of NO2 and PM concentrations in addition to the exhaust temperatures and the flow rates. Thus the engine combustion strategy affects exhaust characteristics which has an impact on the CPF operation and PM mass retained and oxidized. In this report, a process has been developed to simulate the relationship between engine calibration, performance and HC and PM oxidation in the DOC and CPF respectively. Fuel Rail Pressure (FRP) and Start of Injection (SOI) sweeps were carried out at five steady state engine operating conditions. This data, along with data from a previously carried out surrogate HD-FTP cycle [1], was used to create a transfer function model which estimates the engine out emissions, flow rates, temperatures for varied FRP and SOI over a transient cycle. Four different calibrations (test cases) were considered in this study, which were simulated through the transfer function model and the DOC model [1, 2]. The DOC outputs were then input into a model which simulates the NO2 assisted and thermal PM oxidation inside a CPF. Finally, results were analyzed as to how engine calibration impacts the engine fuel consumption, HC oxidation in the DOC and the PM oxidation in the CPF. Also, active regeneration for various test cases was simulated and a comparative analysis of the fuel penalties involved was carried out.

Development of a 1-D Catalyzed Diesel Particulate Filter Model for Simulation of the Performance and the Oxidation of Particulate Matter and Nitrogen Oxides Using Passive Oxidation and Active Regeneration Engine Experimental Data

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.

AN EXPERIMENTAL INVESTIGATION INTO THE EFFECTS OF BIODIESEL BLENDS ON PARTICULATE MATTER OXIDATION IN A CATALYZED PARTICULATE FILTER DURING ACTIVE REGENERATION

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.

Dynamic modeling of active regeneration in catalyzed and non-catalyzed diesel particulate filters

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.

EXPERIMENTAL INVESTIGATION INTO PARTICULATE MATTER DISTRIBUTION IN CATALYZED PARTICULATE FILTERS USING A 3D TERAHERTZ WAVE SCANNER

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.

Two dimensional Lattice Boltzmann simulation of fluid flow through an idealized micro-structure of disordered media

This technical report discusses the application of Lattice Boltzmann Method (LBM) in the fluid flow simulation through porous filter-wall of disordered media. The diesel particulate filter (DPF) is an example of disordered media. DPF is developed as a cutting edge technology to reduce harmful particulate matter in the engine exhaust. Porous filter-wall of DPF traps these soot particles in the after-treatment of the exhaust gas. To examine the phenomena inside the DPF, researchers are looking forward to use the Lattice Boltzmann Method as a promising alternative simulation tool. The lattice Boltzmann method is comparatively a newer numerical scheme and can be used to simulate fluid flow for single-component single-phase, single-component multi-phase. It is also an excellent method for modelling flow through disordered media. The current work focuses on a single-phase fluid flow simulation inside the porous micro-structure using LBM. Firstly, the theory concerning the development of LBM is discussed. LBM evolution is always related to Lattice gas Cellular Automata (LGCA), but it is also shown that this method is a special discretized form of the continuous Boltzmann equation. Since all the simulations are conducted in two-dimensions, the equations developed are in reference with D2Q9 (two-dimensional 9-velocity) model. The artificially created porous micro-structure is used in this study. The flow simulations are conducted by considering air and CO2 gas as fluids. The numerical model used in this study is explained with a flowchart and the coding steps. The numerical code is constructed in MATLAB. Different types of boundary conditions and their importance is discussed separately. Also the equations specific to boundary conditions are derived. The pressure and velocity contours over the porous domain are studied and recorded. The results are compared with the published work. The permeability values obtained in this study can be fitted to the relation proposed by Nabovati [8], and the results are in excellent agreement within porosity range of 0.4 to 0.8.

DYNAMIC MODEL BASED STATE ESTIMATION IN A HEAVY DUTY DIESEL AFTERTREATMENT SYSTEM FOR ONBOARD DIAGNOSTICS AND CONTROLS

Estimating un-measurable states is an important component for onboard diagnostics (OBD) and control strategy development in diesel exhaust aftertreatment systems. This research focuses on the development of an Extended Kalman Filter (EKF) based state estimator for two of the main components in a diesel engine aftertreatment system: the Diesel Oxidation Catalyst (DOC) and the Selective Catalytic Reduction (SCR) catalyst. One of the key areas of interest is the performance of these estimators when the catalyzed particulate filter (CPF) is being actively regenerated. In this study, model reduction techniques were developed and used to develop reduced order models from the 1D models used to simulate the DOC and SCR. As a result of order reduction, the number of states in the estimator is reduced from 12 to 1 per element for the DOC and 12 to 2 per element for the SCR. The reduced order models were simulated on the experimental data and compared to the high fidelity model and the experimental data. The results show that the effect of eliminating the heat transfer and mass transfer coefficients are not significant on the performance of the reduced order models. This is shown by an insignificant change in the kinetic parameters between the reduced order and 1D model for simulating the experimental data. An EKF based estimator to estimate the internal states of the DOC and SCR was developed. The DOC and SCR estimators were simulated on the experimental data to show that the estimator provides improved estimation of states compared to a reduced order model. The results showed that using the temperature measurement at the DOC outlet improved the estimates of the CO , NO , NO2 and HC concentrations from the DOC. The SCR estimator was used to evaluate the effect of NH3 and NOX sensors on state estimation quality. Three sensor combinations of NOX sensor only, NH3 sensor only and both NOX and NH3 sensors were evaluated. The NOX only configuration had the worst performance, the NH3 sensor only configuration was in the middle and both the NOX and NH3 sensor combination provided the best performance.

Quickbird satellite imagery for riparian management : characterizing riparian filter strips and detecting concentrated flow in an agricultural watershed

Riparian ecology plays an important part in the filtration of sediments from upland agricultural lands. The focus of this work makes use of multispectral high spatial resolution remote sensing imagery (Quickbird by Digital Globe) and geographic information systems (GIS) to characterize significant riparian attributes in the USDA’s experimental watershed, Goodwin Creek, located in northern Mississippi. Significant riparian filter characteristics include the width of the strip, vegetation properties, soil properties, topography, and upland land use practices. The land use and vegetation classes are extracted from the remotely sensed image with a supervised maximum likelihood classification algorithm. Accuracy assessments resulted in an acceptable overall accuracy of 84 percent. In addition to sensing riparian vegetation characteristics, this work addresses the issue of concentrated flow bypassing a riparian filter. Results indicate that Quickbird multispectral remote sensing and GIS data are capable of determining riparian impact on filtering sediment. Quickbird imagery is a practical solution for land managers to monitor the effectiveness of riparian filtration in an agricultural watershed.

High temperature, low cycle fatigue of a hybrid particulate/fiber aluminum metal-matrix composite

The effect of shot particles on the high temperature, low cycle fatigue of a hybrid fiber/particulate metal-matrix composite (MMC) was studied. Two hybrid composites with the general composition A356/35%SiC particle/5%Fiber (one without shot) were tested. It was found that shot particles acting as stress concentrators had little effect on the fatigue performance. It appears that fibers with a high silica content were more likely to debond from the matrix. Final failure of the composite was found to occur preferentially in the matrix. SiC particles fracture progressively during fatigue testing, leading to higher stress in the matrix, and final failure by matrix overload. A continuum mechanics based model was developed to predict failure in fatigue based on the tensile properties of the matrix and particles. By accounting for matrix yielding and recovery, composite creep and particle strength distribution, failure of the composite was predicted.

Modeling particulate organic matter diagenesis with SED2K

Diagenesis of particulate organic matter in lake sediments consumes and produces chemical species that have significant effects on water quality, e.g. oxygen and nitrate depletion and attendant mediation of nutrient and metal recycling. A mechanistic, mass balance model (SED2K) is applied here in quantifying the time course and magnitude of sediment response to reductions in depositional fluxes of organic matter. In applying the model, direct, site-specific measurements of the sedimentation and POM rates in Onondaga Lake are used, leaving only the diagenesis coefficient (solubilization) for estimation by fit to downcore POM profiles. Model calibration is constrained by the dual requirement that both POM profiles and the time series of efflux of the products of diagenesis must be matched. Simulations point to the existence of POM preservation processes at depth, a phenomenon that may enhance the timing and magnitude of lake recovery.

Kalman Filter approaches on crane swing

The purpose of this study is to explore a Kalman Filter approach to estimating swing of crane-suspended loads. Measuring real-time swing is needed to implement swing damping control strategies where crane joints are used to remove energy from a swinging load. The typical solution to measuring swing uses an inertial sensor attached to the hook block. Measured hook block twist is used to resolve the other two sensed body rates into tangential and radial swing. Uncertainty in the twist measurement leads to inaccurate tangential and radial swing calculations and ineffective swing damping. A typical mitigation approach is to bandpass the inertial sensor readings to remove low frequency drift and high frequency noise. The center frequency of the bandpass filter is usually designed to track the load length and the pass band width set to trade off performance with damping loop gain. The Kalman Filter approach developed here allows all swing motions (radial, tangential and twist) to be measured without the use of a bandpass filter. This provides an alternate solution for swing damping control implementation. After developing a Kalman Filter solution for a two-dimensional swing scenario, the three-dimensional system is considered where simplifying assumptions, suggested by the two-dimensional study, are exploited. One of the interesting aspects of the three-dimensional study is the hook block twist model. Unlike the mass-independence of a pendulum's natural frequency, the twist natural frequency depends both on the pendulum length and the load’s mass distribution. The linear Kalman Filter is applied to experimental data demonstrating the ability to extract the individual swing components for complex motions. It should be noted that the three-dimensional simplifying assumptions preclude the ability to measure two "secondary" hook block rotations. The ability to segregate these motions from the primary swing degrees of freedom was illustrated in the two-dimensional study and could be included into the three-dimensional solution if they were found to be important for a particular application.