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The differences in hydrocarbons (HCs) emitted by gasoline (E0) and ethanol (EtOH) blend fuels from flex-fuel capable engines can lead to differences in the performance of aftertreatment devices. Vehicle emission results have shown either better performance on E0 compared to E85 or vice versa, dependent on the vehicle calibration. In order to separate the impact of the vehicle and the catalyst, a laboratory study was conducted to evaluate performance on a pulse-flame (pulsator) reactor and compare reactivity towards E0 and E85 (85% EtOH-15% E0) exhaust. The catalysts evaluated were substrate-only, washcoat-only and fully formulated catalysts that had been aged either on a pulsator reactor or dynamometer engine. Catalyst performance was evaluated with light-off tests utilizing both slow and fast temperature ramp rates.

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.

The mechanism for the purging of a lean NOx trap has been investigated. For realistic purge times (e.g., 2 to 5 seconds), the stored NOx species do not decompose simply from equilibrium considerations (i.e., from the drop in O2 and NO concentrations during the rich purge). Instead, the decomposition of stored NOx is promoted by the reductants in the exhaust by a process referred to as reductive elimination. H2 is far more effective than CO or C3H6 for promoting this reductive elimination, particularly at low temperatures (e.g., 250°C). As long as H2 is available in the feedgas, H2O does not participate in the reductive elimination. However, if CO is the only reductant, H2O is needed to convert some of the CO to H2 through the water-gas-shift reaction. H2O is also important for the efficient storage of NOx during lean operation, possibly by enhancing the spillover of NO2 from a precious metal site to a NOx storage site.

A one-dimensional two-phase model of an adsorptive catalytic monolith reactor is used to analyze the Lean NOx Trap (LNT). The model simulates the features of NOx storage and reduction (NSR), a periodic process involving the sequential trapping on a storage component and conversion of NOx to nitrogen on a precious metal catalyst under lean conditions found in the exhaust of lean burn and diesel vehicles. A detailed storage kinetic model is used for the simulations. The NOx storage phase on Pt/BaO/Alumina catalyst has been studied in detail with particular attention to the effect of fluid velocity, storage time and storage component loading. The reductive phase is also analyzed. The simulated results are compared with our lab experimental data. The model predictions are in good agreement with the experimental observations and trends reported in the literature.

A one-dimensional two-phase model of an adsorptive catalytic monolith reactor (used as Lean NOx Trap, LNT) is developed and analyzed. The model simulates the features of NOx storage and reduction (NSR), a periodic process involving the sequential trapping on a storage component and conversion of NOx to nitrogen under lean conditions found in the exhaust of lean burn and diesel vehicles. The effect of design and operating parameters, such as the lean and rich times and feed temperature, on NO2 conversion is examined. Using a relatively simple kinetic model and without any attempt to fit data, the LNT model predicts the dependencies of NO2 conversion on several feed parameters that are in good agreement with experimental observations.