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In order to further characterize and optimize the performance of Selective Catalytic Reduction (SCR) aftertreatment systems used on heavy-duty diesel engines, an accurately calibrated high-fidelity multi-step global kinetic SCR model and a reduced order estimator for on-board diagnostic (OBD) and control are desirable. In this study, a Cu-zeolite SCR catalyst from a 2010 Cummins ISB engine was experimentally studied in a flow reactor using carefully designed protocols. A 2-site SCR model describing mass transfer and the SCR chemical reaction mechanisms is described in the paper. The model was calibrated to the reactor test data sets collected under temperatures from 200 to 425 °C and SCR space velocities of 60000, 90000, and 120000 hr-1. The model parameters were calibrated using an optimization code to minimize the error between measured and simulated NO, NO₂, N₂O, and NH₃ gas concentration time histories.

Model-based control strategies are important for meeting the dual objective of maximizing NOx reduction and minimizing NH3 slip in urea-SCR catalysts. To be implementable on the vehicle, the models should capture the essential behavior of the system, while not being computationally intensive. This paper discusses the adequacy of two different reduced order SCR catalyst models and compares their performance with a higher order model. The higher order model assumes that the catalyst has both diffusion and reaction kinetics, whereas the reduced order models contain only reaction kinetics. After describing each model, its parameter identification and model validation based on experiments on a Navistar I6 7.6L engine are presented. The adequacy of reduced order models is demonstrated by comparing the NO, NO2 and NH3 concentrations predicted by the models to their concentrations from the test data.

A high-fidelity multi-step global kinetic Selective Catalytic Reduction (SCR) model which can predict SCR performance in engine exhaust systems is desirable for optimizing the SCR system, designing on-vehicle control systems and on-board diagnostic (OBD) functions. In this study, a Cu-zeolite SCR catalyst in the exhaust of a 2010 Cummins 6.7L ISB diesel engine was experimentally studied under both steady-state and transient conditions. Steady-state engine tests spanned SCR inlet temperatures from 250 to 400°C with a constant space velocity of 60 khr-1. A 1-D Cu-zeolite model originally developed from reactor data was improved and calibrated to the steady-state engine experimental data. The calibrated model is capable of predicting NO/NO₂ reduction, NH₃ slip, and NH₃ storage associated phenomena.

Current legislative trends regarding diesel emissions are striving to achieve two seemingly competing goals: simultaneously lowering NOx and greenhouse gas (GHG) emissions. These two goals are considered at odds since lower GHG emissions (e.g. CO2) is achieved via high combustion efficiency that result in higher engine out NOx emissions and lower exhaust gas temperatures [1, 2]. Conversely, NOx reduction technologies such as SCR require temperatures above 200°C for dosing the reductant (DEF) [3, 4, 5] as well as for high conversion efficiencies [1, 2, 6, 7, 8, 9]. Dosing DEF requires injection pressures around 5 bar to ensure proper penetration into the exhaust stream as well as generate the appropriate spray pattern and droplet sizes. Dosing DEF generally requires long mixing and/or high turbulence (high restriction) areas so that the aqueous urea solution can be converted into gaseous NH3 without deposit formation [8, 10, 11, 12, 13, 14, 15].

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.

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.

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.

Selective catalytic reduction (SCR) systems are in use on heavy duty diesel engines for NOx control. An SCR NOx reduction efficiency of higher than 95% is required to meet the proposed increasingly stringent NOx emission standards and the 2014-2018 fuel consumption regulations. The complex engine exhaust conditions including the nonuniformity of temperature, flow, and maldistribution of NH3 present at the catalyst inlet need to be considered for improved performance of the SCR system. These factors cause the SCR to underperform negatively impacting the NOx reduction efficiency as well as the NH3 slip. In this study, the effects of the nonuniformity of temperature, flow velocity and maldistribution of NH3 on the SCR performance were investigated using 1-dimensional (1D) model simulations for a Cu-zeolite SCR. The model was previously calibrated and validated to reactor and steady-state and transient engine experimental data.