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A set of elementary surface reactions is proposed for modeling the chemistry in a lean NOx trap during regeneration (reduction of stored NOx). The proposed reaction mechanism can account for the observed product distribution from the trap over a range of temperatures and inlet gas compositions similar to those expected for realistic operation. The mechanism includes many reactions already discussed in the literature, together with some hypothesized reactions that are required to match observations from temperature programmed reactor experiments with a commercial lean NOx trap catalyst. Preliminary results indicate that the NOx trap regeneration and byproduct formation rates can be effectively captured by using a relatively compact set of elementary reactions.

We study the NOx storage process in lean NOx traps using bench-flow experiments and simulated diesel exhaust. Given that formulation alone is an inadequate indicator of performance (due to the effects of manufacturing processes) a minimal set of experiments is always needed to compare the performance of LNTs. We define simple performance measures based on such a set of experiments that can be used to compare lean phase operations of various LNTs under various conditions concisely. Though the noble metal sites are essential for storage, the benefits of increasing noble metal loading start to wane beyond a certain limit. Our experiments suggest a possibility that a lean NOx reduction reaction may be occuring in LNTs. If this reaction is confirmed further in future experiments, its products need to be identified. The sorbent shifts the equilibrium between NO and NO2 towards NO.

We consider the effect of intra-channel mass and heat transfer in modeling the performance of diesel oxidation catalysts. Many modeling studies have assumed that the intra-channel flow is laminar and, thus, heat and mass transfer between the bulk gas and wall are appropriately described using correlations for fully-developed laminar flow. However, recent experimental measurements of CO and hydrocarbon oxidation in diesel exhaust reveal that actual mass-transfer rates can deviate significantly from those predicted by such correlations. In particular, it is apparent that there is a significant dependence of the limiting mass-transfer rate on the channel Reynolds number. Other studies in the literature have revealed similar behavior for heat transfer. We speculate that this Reynolds number dependence results from boundary-layer disturbances associated with washcoat surface roughness and/or porosity.

In this paper we summarize preliminary results from applying a new mathematical technique- chaotic time series analysis (CTSA)- to cylinder pressure data from a spark-ignition (SI) four-stroke engine fueled with both methanol and iso-octane. Our objective is to look for the presence of “deterministic chaos” dynamics in peak pressure variations and to investigate the potential usefulness of CTSA as a diagnostic tool. Our results suggest that sequential peak cylinder pressures exhibit some characteristic features of deterministic chaos and that CTSA can extract previously unrecognized information from such data.

This paper describes the reduction of cyclic combustion variations in spark-ignited engines, especially under idle conditions in which the air-fuel mixture is lean of stoichiometry. Under such conditions, the combination of residual cylinder gas and parametric variations (such as variations in fuel preparation) gives rise to significant combustion instabilities that may lead to customer-perceived engine roughness and transient emissions spikes. Such combustion instabilities may preclude operation at air-fuel ratios that would otherwise be advantageous for fuel economy and emissions. This approach exploits the recognition that a component of the observed combustion instability results from a noise-driven, nonlinear deterministic mechanism that can be actively stabilized by small feedback control actions which result in little if any additional use of fuel.

We propose a simple, physically oriented model that explains important characteristics of cyclic combustion variations in spark-ignited engines. A key model feature is the interaction between stochastic, small-scale fluctuations in engine parameters and nonlinear deterministic coupling between successive engine cycles. Prior-cycle effects are produced by residual cylinder gas which alters volume-average in-cylinder equivalence ratio and subsequent combustion efficiency. The model's simplicity allows rapid simulation of thousands of engine cycles, permitting in-depth statistical studies of cyclic variation patterns. Additional mechanisms for stochastic and prior-cycle effects can be added to evaluate their impact on overall engine performance. We find good agreement with our experimental data.