Modeling of the Catalyzed Continuously Regenerating Diesel Particulate Filter (CCR-DPF) System: Model Development and Passive Regeneration Studies 2007-01-0043

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. This Catalyzed DPF (CDPF) in combination with an upstream Diesel Oxidation Catalyst (DOC) is known as a Catalyzed Continuously Regenerating Trap (CCRT^®) [3], and will henceforth be referred to as the CCR-DPF.

A model describing the performance of the CCR-DPF has been developed. This model comprises a 1-D DOC model based on laboratory microreactor data, and a 1-D single channel pair model of a catalyzed DPF. The latter itself is made up of two parts: i) a model describing axial flow in the channels, and temperature effects in the filter; and ii) a description of soot accumulation and removal, NO oxidation within the filter wall, and NO₂ diffusion from the wall to the soot cake. Langmuir-Hinshelwood expressions were employed to describe the platinum based DOC reaction kinetics; this model has been validated using engine bench data. The catalyzed DPF model has also been validated using engine bench data.

These two models have been combined to create a full model of the CCR-DPF system, which can be used to aid in system design for many applications.