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Urea-selective catalytic reduction (SCR) after-treatment systems are used for reducing oxides of nitrogen (NOx) emissions in medium and heavy duty diesel vehicles. This paper addresses control-oriented modeling, starting from first-principles, of SCR after-treatment systems. Appropriate simplifications are made to yield governing equations of the Urea-SCR. The resulting nonlinear partial differential equations (PDEs) are discretized and linearized to yield a family of linear finite-dimensional state-space models of the SCR at different operating points. It is further shown that this family of models can be reduced to three operating regions. Within each region, parametric dependencies of the system on physical mechanisms are derived. Further model reduction is shown to be possible in each of the three regions resulting in a second-order linear model with sufficient accuracy.

For urea Selective Catalytic Reduction (SCR) systems, adaptive control is of interest to provide a capability of maintaining high NOx conversion efficiency and low ammonia slip in the presence of uncertainties in the system. In this paper, the dynamics of the urea SCR system are represented by a control-oriented model which is based on a linear transfer function, with parameters dependent on engine operating conditions. The parameters are identified from input-output data generated by a high fidelity full chemistry model of the urea SCR system. The use of the full chemistry model facilitated the representation of the dynamics of stored ammonia (not a directly measurable parameter) as well as post SCR NOx and ammonia slip. A closed-loop Proportional-plus-Integral (PI) controller was first designed using the estimate of stored ammonia as a feedback signal.

Ignoring the impact of water condensation leads to incorrect temperature simulation during cold start, and this can lead to questions being raised about the overall accuracy of aftertreatment simulation tools for both temperature and emission predictions. This report provides a mathematical model to simulate the condensation and evaporation of water in exhaust after-treatment devices. The simulation results are compared with experimental data. Simulation results show that the temperature profiles obtained using the condensation model are more accurate than the profiles obtained without using the condensation model. The model will be very useful in addressing questions that concern the accuracy of the simulation tool during cold-start and heating up of catalysts, which accounts for the conditions where tailpipe emission issues are most significant.

Engine operating strategies typically geared towards higher fuel economy and lower NOx widely affect exhaust composition and temperature. These exhaust variables critically drive the performance of After Treatment (AT) components, and hence should guide their screening and selection. Towards this end, the effect of H2 level in diesel exhaust on the performance of a Diesel Oxidation Catalyst (DOC) was studied using flow reactor experiments, vehicle emission measurements and mathematical models. Vehicle chassis dynamometer data showed that exhaust from light-duty and heavy-duty diesel trucks contained very little to almost no H2 (FTP average CO/H2 ∼ 40 to 70) as compared to that of a gasoline car exhaust (FTP average CO/H2 ∼ 3). Two identical flow reactor experiments, one with H2 (at CO/H2 ∼ 3) and another with no H2 in the feed were designed to screen DOCs under simulated feed gas conditions that mimicked these two extremes in the exhaust H2 levels.

A typical diesel After-Treatment (AT) system to meet 2010 North American regulations consists of a Diesel Oxidation Catalyst (DOC) for oxidizing Hydrocarbons (HCs) and Carbon Monoxide (CO), followed by a Selective Catalytic Reduction (SCR) catalyst for NOx reduction, and a diesel particulate filter. DOCs are also used to oxidize NO in the exhaust to NO2 that substantially improves low-temperature SCR NOx reduction performance. Vehicle and engine dynamometer data under typical operating conditions show (1) engine-out NO2/NOx can be as high as 40%, (2) DOC can reduce NO2 to NO in the presence of reductants, and (3) an aged DOC with a low CO/HC conversion can be a net consumer of NO2 over a wide range of temperatures and space velocities. Flow reactor experiments simulating diesel exhaust conditions show that DOC-out NO2 is independent of the inlet NO2/NOx in the feed.

The high conversion efficiency required by the modern three-way catalyst (TWC) is dependent on oxygen storage material functionality and capacity. To successfully model a TWC, it is critical that the oxygen storage function in the catalyst be adequately represented. The original oxygen storage model (a simple “bucket” model) included in one of Ford's TWC models, SIMTWC, was developed for vehicle programs meeting LEV emission standards. Application of SIMTWC to test data from vehicles targeting more stringent emission standards, such as ULEV and PZEV, revealed limitations in the accuracy of the original bucket model. To address these limitations, an improved kinetic model of oxygen storage is being developed. This new model is more kinetically-detailed than the old model.

This paper presents the development of an analytical model that complements laboratory based experiments to provide a tool for Selective Catalyst Reduction (SCR) applications. The model calibration is based on measured data from NOx reduction performance tests as well as ammonia (NH3) adsorption/desorption tests over select SCR catalyst formulations in a laboratory flow reactor. Only base metal/zeolite SCR samples were evaluated. Limited validations are presented that show the model agrees well with vehicle data from Environmental Protection Agency Federal Test Procedure (EPA FTP) emission assessments. The model includes energy and mass balances, several different NH3 reactions with NOx, NH3 adsorption and desorption algorithms, and NH3 oxidation.

This paper presents a study of urea SCR catalyst aging characteristics and implementation into an analytical model that complements laboratory based experiments for a dynamometer-aged SCR brick. The model calibration is based on measured data taken from a 120k-mile simulated dynamometer-aged base metal/zeolite SCR. Dynamometer aging led to non-uniform axial deterioration with more severe deactivation toward the front of the SCR brick compared to the rear. Data from a 120k-mile simulated hydrothermally oven-aged SCR (uniform axial aging) is used to establish baseline aged NOx performance and NH3 adsorption/desorption behavior. An axial deterioration factor is applied to the baseline model to account for differences between oven and dynamometer aging. The model is exercised using engine out vehicle data to examine how different aging processes (oven vs. dynamometer) affect overall NOx performance during the EPA FTP (Environmental Protection Agency Federal Test Procedure).

This paper presents a hybrid approach for developing a robust model of a diesel oxidation catalyst (DOC). Information from multiple sources including detailed thermal balances, laboratory performance data, phenomenological description of adsorption and desorption in catalyst pores, and experience based correlations are seamlessly integrated using optimization and statistical tools to create an easy-to-use, computationally inexpensive predictive model. Light-off, Light-out, and fuel quench data from a diesel pulsator and engine dynamometer are used for model calibration. The calibrated model predicts cumulative HC and CO tailpipe vehicle emissions as well as DOC NOx outlet composition (NO vs. NO2).

The trapping and regeneration behaviors of a diesel particulate filter (DPF), including particle size, are examined via engine dynamometer testing. The exhaust system consists of two active lean NOx (ALN) catalysts in series followed by a catalyzed DPF. Forced regenerations are accomplished by injecting diesel fuel into the exhaust in front of the ALN catalysts to generate an exotherm sufficient to induce soot oxidation. Results are reported for two diesel fuels, one with 340 ppm sulfur, and the other with 4 ppm sulfur, and as a function of DPF regeneration temperature. The results show the DPF to be very effective at removing particulate matter, >99% efficiency. The <1% of particles that escape trapping exhibit a size distribution very similar to engine out soot. During regeneration, particle emissions remain well below engine out levels for the low sulfur fuel, but exhibit a temporary nucleation mode of about ten times the engine out level for the high sulfur fuel.

Ford Motor Company is participating in the Department of Energy's (DOE) Ultra-Clean Transportation Fuels Program with the goal to explore the development of innovative emission control systems for advanced compression-ignition direct-injection (CIDI) transportation engines. CIDI (or diesel) engines have the advantages of a potential 40% fuel economy improvement and 20% less CO2 emissions than current gasoline counterparts. To support this goal, Ford plans to demonstrate an exhaust emission control system that provides high efficiency particulate matter (PM) and NOx reduction. Very low sulfur diesel fuel will be used to enable low PM emissions, reduce the fuel economy penalty associated with the emission control system, and increase the long-term durability of the system. The end result will allow vehicles with CIDI engines to be Tier II emissions certified at a minimum cost to the consumer.

Projected NOx and fuel costs are compared for a plasma-catalyst system and an active lean NOx catalyst system. Comparisons are based on modeling of FTP cycle performance. The model uses steady state laboratory device characteristics, combined with measured vehicle exhaust data to predict NOx conversion efficiency and fuel economy penalties. The plasma system uses a proprietary catalyst downstream of a plasma discharge. The active lean NOx catalyst uses a catalyst along with addition of hydrocarbons to the exhaust. For the plasma catalyst system, NOx conversion is available over a wide temperature range. Increased electrical power improves conversion but degrades vehicle fuel economy; 10 J/L energy deposition costs roughly 3% fuel economy. Improved efficiency is also available with larger catalyst size or increased exhaust hydrocarbon content. For the active lean NOx system, NOx conversion is available only in a narrow temperature range.

The optimized design of an exhaust emission system in terms of performance, cost, packaging, and engine control strategy will be a key part of competitively meeting future more stringent emission standards. Extensive use of vehicle experiments to evaluate design system tradeoffs is far too time consuming and expensive. Imperative to successfully meeting the challenges of future emission regulations and cost constraints is the development of an exhaust system simulation model which offers the ability to sort through major design alternatives quickly while assisting in the interpretation of experimental data. Previously, detailed catalyst models have been developed which require the specification of intricate kinetic mechanisms to determine overall catalyst performance. While yielding extremely valuable results, these models use complex numerical algorithms to solve multiple partial differential equations which are time consuming and occasionally numerically unstable.