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Diesel Oxidation Catalysts (DOC) are used on heavy duty diesel engine applications and experience large internal temperature variations from 150 to 600°C. The DOC oxidizes the CO and HC in the exhaust to CO2 and H2O and oxidizes NO to NO2. The oxidation reactions are functions of its internal temperatures. Hence, accurate estimation of internal temperatures is important both for onboard diagnostic and aftertreatment closed loop control strategies. This paper focuses on the development of a reduced order model and an Extended Kalman Filter (EKF) state estimator for a DOC. The reduced order model simulation results are compared to experimental data. This is important since the reduced order model is used in the EKF estimator to predict the CO, NO, NO2 and HC concentrations in the DOC and at the outlet. The estimator was exercised using transient drive cycle engine data. The closed loop EKF improves the temperature estimate inside the DOC compared to the open loop estimator.

Numerical models of aftertreatment devices are increasingly becoming indispensable tools in the development of aftertreatment systems that enable modern diesel engines to comply with exhaust emissions regulations while minimizing the cost and development time involved. Such a numerical model was developed at Michigan Technological University (MTU) [1] and demonstrated to be able to simulate the experimental data [2] in predicting the characteristic pressure drop and PM mass retained during passive oxidation [3] and active regeneration [4] of a catalyzed diesel particulate filter (CPF) on a Cummins ISL engine. One of the critical aspects of a calibrated numerical model is its usability - in other words, how useful is the model in predicting the pressure drop and the PM mass retained in another particulate filter on a different engine without the need for extensive recalibration.

In this study, a DOC catalyst was experimentally studied in an engine test cell with a2010 Cummins 6.7L ISB diesel and a production aftertreatment system. The test matrix consisted of steady state, active regeneration with in-cylinder fuel dosing and transient conditions. Conversion efficiencies of total hydrocarbon (THC), CO, and NO were quantified under each condition. A previously developed high-fidelity DOC model capable of predicting both steady state and transient active regeneration gaseous emissions was calibrated to the experimental data. The model consists of a single 1D channel where mass and energy balance equations were solved for both surface and bulk gas regions. The steady-state data were used to identify the activation energies and pre-exponential factors for CO, NO and HC oxidation, while the steady-state active regeneration data were used to identify the inhibition factors. The transient data were used to simulate the thermal response of the DOC.

This paper focuses on the development of an Extended Kalman Filter for estimating internal species concentration and storage states of an SCR using NOX and NH₃ sensors. The motivation for this work was twofold. First, knowledge of internal states may be useful for onboard diagnostic strategy development. In particular, significant errors between the outlet NOX or NH₃ sensors, reconstructed from estimated states, and the measured NOX or NH₃ concentrations may aid OBD strategies that attempt to identify particular system failure modes. Second, the EKF described estimates not only stored ammonia but also NO, NO₂ and NH₃ gas concentrations within and exiting the SCR. Exploiting knowledge of the individual species concentrations, instead of lumping them together as NOX, can yield improved closed loop urea controller performance in terms of reduced urea consumption and better NOX conversion.

Numerical modeling of aftertreatment systems has been proven to reduce development time as well as to facilitate understanding of the internal physical and chemical processes occurring during different operating conditions. Such a numerical model for a catalyzed diesel particulate filter (CPF) was developed in this research work which has been improved from an existing numerical model briefly described in reference. The focus of this CPF model was to predict the effect of the catalyst on the gaseous species concentrations and to develop particulate matter (PM) filtration and oxidation models for the PM cake layer and substrate wall so as to develop an overall model that accurately predicts the pressure drop and PM oxidized during passive oxidation and active regeneration. Descriptions of the governing equations and corresponding numerical methods used with relevant boundary conditions are presented.

Active regeneration experiments were performed on a production diesel aftertreatment system containing a diesel oxidation catalyst and catalyzed particulate filter (CPF) using blends of soy-based biodiesel. The effects of biodiesel on particulate matter oxidation rates in the filter were explored. These experiments are a continuation of the work performed by Chilumukuru et al., in SAE Technical Paper No. 2009-01-1474, which studied the active regeneration characteristics of the same aftertreatment system using ultra-low sulfur diesel fuel. Experiments were conducted using a 10.8 L 2002 Cummins ISM heavy-duty diesel engine. Particulate matter loading of the filter was performed at the rated engine speed of 2100 rpm and 20% of the full engine load of 1120 Nm. At this engine speed and load the passive oxidation rate is low. The 17 L CPF was loaded to a particulate matter level of 2.2 g/L.

A quasi-steady 1-dimensional computer model of a catalyzed particulate filter (CPF) capable of simulating active regeneration of the CPF via diesel fuel injection upstream of a diesel oxidation catalyst (DOC) or other means to increase the exhaust gas temperature has been developed. This model is capable of predicting gaseous species concentrations (HC's, CO, NO and NO2) and exhaust gas temperatures within and after the CPF, for given input values of gaseous species and PM concentrations before the CPF and other inlet variables such as time-varying temperature of the exhaust gas at the inlet of the CPF and volumetric flow rate of exhaust gas.

Active regeneration of a catalyzed particulate filter (CPF) is affected by a number of parameters specifically particulate matter loading and inlet temperature. The MTU 1-D 2-Layer CPF model [1] was used to analyze these effects on the pressure drop, oxidation and filtration characteristics of a CPF during active regeneration. In addition, modeling results for post loading experiments were analyzed to understand the difference between loading a clean filter as compared to a partially regenerated filter. Experimental data obtained with a production Cummins regenerative particulate filter for loading, active regenerations and post loading experiments were used to calibrate the MTU 1-D 2-Layer CPF model. The model predicted results are compared with the experimental data and were analyzed to understand the CPF characteristics during active regeneration at 1.1, 2.2 and 4.1 g/L particulate matter (PM) loading and CPF inlet temperatures of 525, 550 and 600°C.

Steady state loading characterization experiments were conducted at three different engine load conditions and rated speed on the cracked catalyzed particulate filter (CPF). The experiments were performed using a 10.8 L 2002 Cummins ISM-330 heavy duty diesel engine. The CPF underwent a ring off failure, commonly seen in particulate filters, due to high radial and axial temperature gradients. The filters were cracked during baking in an oven which was done to regenerate PM collected after every loading characterization experiment. Two different configurations i.e. with and without a diesel oxidation catalyst (DOC) upstream of the CPF were studied. The data were compared with that on an un-cracked CPF at similar engine conditions and configurations. Pressure drop, transient filtration efficiency by particle size and PM mass and gaseous emissions measurements were made during each experiment.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.

Steady-state particulate loading experiments were conducted on an advanced production catalyzed particulate filter (CPF), both with and without a diesel oxidation catalyst (DOC). A heavy-duty diesel engine was used for this study with the experiments conducted at 20, 40, 60 and 75 % of full load (1120 Nm) at rated speed (2100 rpm). The data obtained from these experiments were used and are necessary for calibrating the MTU 1-D 2-Layer CPF model. These experimental and modeling results were compared to previous research conducted at MTU that used the same engine but an earlier development version of the combination of DOC and CPF. The motivation for the comparison of the two systems was to determine whether the reformulated production catalysts performed as good or better than the early development catalysts. The results were compared to understand the filtration and oxidation differences between the two DOC+CPF and the CPF-only aftertreatment systems.

A Cummins ISB 5.9 liter medium-duty engine with cooled EGR has been used to study an early extrusion of an advanced ceramic uncatalyzed diesel particulate filter (DPF). Data for the advanced ceramic material (ACM) and an uncatalyzed cordierite filter of similar dimensions are presented. Pressure drop data as a function of mass loadings (0, 4, and 6 grams of particulate matter (PM) per liter of filter volume) for various flow rate/temperature combinations (0.115 - 0.187 kg/sec and 240 - 375 °C) based upon loads of 15, 25, 40 and 60% of full engine load (684 N-m) at 2300 rpm are presented. The data obtained from these experiments were used to calibrate the MTU 1-D 2-Layer computer model developed previously at MTU. Clean wall permeability determined from the model calibration for the ACM was 5.0e-13 m2 as compared to 3.0e-13 m2 for cordierite.

A methodology to estimate the mass of particulate retained in a catalyzed particulate filter as a function of measured total pressure drop, volumetric flow rate, exhaust temperature, exhaust gas viscosity and cake and wall permeability applicable to real-time computation is discussed. This methodology is discussed from the view point of using it to indicate when to initiate active regeneration and as an On-Board Diagnostic tool to detect filter failures. Steady-state loading characterization experiments were conducted on a catalyzed diesel particulate filter (CPF) in a Johnson Matthey CCRT® (catalyzed continuously regenerating trap) system. The experiments were performed using a 10.8 L 2002 Cummins ISM heavy-duty diesel engine. Experiments were conducted at 20, 60 and 75% of full engine load (1120 Nm) and rated speed (2100 rpm) to measure the pressure drop, transient filtration efficiency, particulate mass balance, and gaseous emissions.

An experimental and modeling study was conducted to study the passive regeneration of a catalyzed particulate filter (CPF) by the oxidation of particulate matter (PM) via thermal and Nitrogen dioxide/temperature-assisted means. Emissions data in the exhaust of a John Deere 6.8 liter, turbocharged and after-cooled engine with a low-pressure loop EGR and a diesel oxidation catalyst (DOC) - catalyzed particulate filter (CPF) in the exhaust system was measured and used for this study. A series of experiments was conducted to evaluate the performance of the DOC, CPF and DOC+CPF configurations at various engine speeds and loads.

An experimental and computational study was performed to evaluate the performance of the CRT™ technology with an off-highway engine with a cooled low pressure loop EGR system. The MTU-Filter 1D DPF code predicts the particulate mass evolution (deposition and oxidation) in a diesel particulate filter (DPF) during simultaneous loading and during thermal and NO2-assisted regeneration conditions. It also predicts the pressure drop across the DPF, the flow and temperature fields, the solid filtration efficiency and the particle number distribution downstream of the DPF. A DOC model was also used to predict the NO2 upstream of the DPF. The DPF model was calibrated to experimental data at temperatures from 230°C to 550°C, and volumetric flow rates from 9 to 39 actual m3/min.

A 1-D 2-layer model developed previously at MTU was used in this research to predict the pressure drop, filtration characteristics and various properties of the particulate filter and the particulate deposit layer. The model was calibrated and validated for this CPF with data obtained from steady state experiments conducted using a 1995 Cummins M11-330E heavy-duty diesel engine with manual EGR and using ULSF. The CPF used is a NGK filter having a cordierite substrate with NEX catalyst type formulation (54% porosity, 15.0 μm mean pore diameter and 50 gms/ft3 Pt). The filter was catalyzed using a wash coat process. The model was used to predict the pressure drop, particulate mass retained inside the CPF, particulate mass filtration efficiency and concentration downstream of the CPF with agreement between the experimental and simulated data.

A 1-D 2-layer model developed previously at MTU was used in this research to predict the pressure drop, filtration characteristics and various properties of the particulate filter and the particulate deposit layer. The model was used along with dilute emission data to characterize two catalyzed particulate filters (CPFs) having different catalyst loading and catalyst application processes. The model was calibrated and validated with data obtained from steady state experiments conducted using a 1995 Cummins M11-330E heavy-duty diesel engine with manual EGR with different fuels for the two different CPFs. The two different catalyzed particulate filters were CPF III (5 gms/ft3 Pt) and CPF V (50 gms/ft3 Pt). Both the CPFs had cordierite substrates with CPF III and CPF V had MEX and NEX catalyst type formulation respectively. The CPF III filter was catalyzed using a solution-impregnated process while the CPF V filter was catalyzed using a wash coat process.

A one-dimensional model simulating the oxidation of CO, HC, and NO was developed to predict the gaseous emissions downstream of a diesel oxidation catalyst (DOC). The model is based on the conservation of mass, species, and energy inside the DOC and draws on past research literature. Steady-state experiments covering a wide range of operating conditions (exhaust temperatures, flow rates and gaseous emissions) were performed, and the data were used to calibrate and validate the model. NO conversion efficiencies of 50% or higher were obtained at temperatures between 300°C and 350°C. CO conversion efficiencies of 85% or higher and HC conversion efficiencies of 75% or higher were found at every steady state condition above 200°C. The model agrees well with the experimental results at temperatures from 200°C to 500°C, and volumetric flow rates from 8 to 42 actual m3/min.

A one-dimensional, two layer computational model was developed to predict the behavior of a clean and particulate-loaded catalyzed wall-flow diesel particulate filter (CPF). The model included the mechanisms of particle deposition inside the CPF porous wall and on the CPF wall surface, the exhaust flow field and temperature field inside the CPF, as well as the particulate catalytic oxidation mechanisms accounting for the catalyst-assisted particulate oxidation by the catalytic coating in addition to the conventional particulate thermal oxidation. The paper also develops the methodology for calibrating and validating the model with experimental data. Steady state loading experiments were performed to calibrate and validate the model.

A 2-dimensional numerical model (MTU-FILTER) for a single channel of a honeycomb ceramic diesel particulate trap has been developed. The mathematical modeling of the filtration, flow, heat transfer and regeneration behavior of the particulate trap is described. Numerical results for the pressure drop and particulate mass were compared with existing experimental results. Parametric studies of the diesel particulate trap were carried out. The effects of trap size and inlet temperature on the trap performance are studied using the trap model. An approximate 2-dimensional analytical solution to the simplified Navier-Stokes equations was used to calculate the velocity field of the exhaust flow in the inlet and outlet channels. Assuming a similarity velocity profile in the channels, the 2-dimensional Navier-Stokes equations are approximated by 1-dimenisonal conservation equations, which is similar to those first developed by Bissett.