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A one-dimensional model of a NOx trap system was developed to describe NOx storage during the lean operation, and NOx release and subsequent reduction during the rich regeneration process. The development of a NOx trap model potentially enables the optimisation of catalyst volume, precious metal loading, substrate type and regeneration strategy for these complex systems. To develop a fundamental description of catalytic activity, experiments were conducted to investigate the key processes involved in isolation (as far as possible), using a Pt/Rh/BaO/Al2O3 model catalyst. A description of the storage capacity as a function of temperature was determined using NOx breakthrough curves and the storage portion of more dynamic lean-rich cycling experiments. NOx breakthrough curves were also used for determination of rate of NOx storage. Kinetics for NOx reduction, as well as CO and HC oxidation, were determined using steady state reactor experiments.

Particulate Matter (PM) emissions are of increasing importance, as diesel emissions legislation continues to tighten around the world. Diesel PM can be controlled using Diesel Particulate Filters (DPFs), which can effectively reduce the level of carbon (soot) emissions to ambient background levels. The Johnson Matthey Continuously Regenerating Trap (CRT®) [1], which will be referred to as the Continuously Regenerating DPF (CR-DPF) for the remainder of this paper, has been widely applied in Heavy Duty Diesel (HDD) applications, and has been proved to have outstanding field durability [2]. To widen the potential application of this system, addition of a platinum based catalyst to the DPF has been shown to lead to a higher PM removal rate under passive regeneration conditions, using the NOx contained in the exhaust gases.

A 1-D numerical model describing the ammonia selective catalytic reduction (SCR) de-NOx process has been developed based on data measured on a laboratory microreactor for a vanadia-titania washcoated catalyst system. Kinetics for various NH3-NOx reactions were investigated, as well as those for ammonia, CO and hydrocarbon oxidation. The model has been successfully validated against engine bench measurements, over light-off and ESC tests, under a wide range of conditions, e.g. flow rate, temperature, NO2/NO ratio, and ammonia injection rate. A very good agreement between the experimental data and the model has been achieved. The model has now been used to predict the effect of NO2/NO ratio on NOx conversion, and the effect of different ammonia injection rates on the efficiency of the SCR process.

Diesel emissions legislation continues to tighten around the world, and Particulate Matter (PM) emissions are currently the focus of much attention. Diesel PM can be controlled using Diesel Particulate Filters (DPFs), which can effectively reduce the level of carbon (soot) emissions to ambient background levels. In the Heavy Duty Diesel (HDD) area, the Continuously Regenerating Trap (CRT®) [1] has been widely applied in the retrofit market. This system will henceforth be referred to as the Continuously Regenerating DPF (CR-DPF). There are currently over 100,000 of these systems in use in retrofit applications worldwide. This system comprises a specially formulated Diesel Oxidation Catalyst (DOC) upstream of a DPF; the NO2 generated by the DOC is used to combust the carbon collected in the DPF at low temperatures. A model describing the performance of the CR-DPF has been developed.

Achieving early catalyst light-off is crucial if stringent emissions standards are to be met; if light-off is late, the emissions limit could be exceeded even before the catalyst starts to work. This paper presents a detailed simulation study of the factors affecting the light-off of a TWC. Simulation is not just faster and cheaper than vehicle testing, it also enables more insight into the factors affecting catalyst performance to be obtained. For example, changing the substrate (cell density and wall thickness) affects the rates of heat and mass transport, as well as the thermal mass of the catalyst. In a vehicle test, all three factors are changed at once, but with a simulation each of these factors can implemented one at time to enable the relative importance of these factors to be determined.