Search Results

The effects of thermal and chemical aging on the performance of cordierite-based and high-porosity mullite-based diesel particulate filters (DPFs), were quantified, particularly their filtration efficiency, pressure drop, and regeneration capability. Both catalyzed and uncatalyzed core-size samples were tested in the lab using a diesel fuel burner and a chemical reactor. The diesel fuel burner generated carbonaceous particulate matter with a pre-specified particle-size distribution, which was loaded in the DPF cores. As the particulate loading evolved, measurements were made for the filtration efficiency and pressure drop across the filter using, respectively, a Scanning Mobility Particle Sizer (SMPS) and a pressure transducer. In a subsequent process and on a different bench system, the regeneration capability was tested by measuring the concentration of CO plus CO2 evolved during the controlled oxidation of the carbonaceous species previously deposited on the DPF samples.

Fuel properties impact the engine-out emission directly. For some geographic regions where diesel engines can meet emission regulations without aftertreatment, the change of fuel properties will lead to final tailpipe emission variation. Aftertreatment systems such as Diesel Particulate Filter (DPF) and Selective Catalytic Reduction (SCR) are required for diesel engines to meet stringent regulations. These regulations include off-road Tier 4 Final emission regulations in the USA or the corresponding Stage IV emission regulations in Europe. As an engine with an aftertreatment system, the change of fuel properties will also affect the system conversion efficiency and regeneration cycle. Previous research works focus on prediction of engine-out emission, and many are based on chemical reactions. Due to the complex mixing, pyrolysis and reaction process in heterogeneous combustion, it is not cost-effective to find a general model to predict emission shifting due to fuel variation.

With stringent emission regulations, aftertreatment systems with a Diesel Particulate Filter (DPF) and a Selective Catalytic Reduction (SCR) are required for diesel engines to meet PM and NOx emissions. The adoption of aftertreatment increases the back pressure on a typical diesel engine and makes engine calibration a complicated process, requiring thousands of steady state testing points to optimize engine performance. When configuring an engine to meet Tier IV final emission regulations in the USA or corresponding Stage IV emission regulations in Europe, this high back pressure dramatically impacts transient performance. The peak NOx, smoke and exhaust temperature during a diesel engine transient cycle, such as the Non-Road Transient Cycle (NRTC) defined by the US Environmental Protection Agency (EPA), will in turn affect the performance of the aftertreatment system and the tailpipe emissions level.

The wall Flow Diesel Particulate Filter (DPF) is one of the major technologies used to meet the current and future Particulate Matter (PM) emission regulations on heavy duty applications. This technology, however, adds significant engine backpressure. This has a negative impact on fuel consumption, and in turn, on CO2emissions. In order to better understand the DPF impact on engine backpressure, a large amount of DPF pressure drop models have been published, especially over the last ten years. Even though each published model has slight variations, they were all derived from Konstandopoulos approach of the problem [1]. However, in 1998, Opris developed a unique pressure drop model [2,4], that is radically different from Konstandopoulos’ method. In the Opris model, Navier-Stockes equations were analytically solved in the context of a DPF. Along with Darcy’s law, and the 2D flow-field solution, a fundamental expression of the DPF pressure drop was obtained.

A predictive numerical model was developed to determine the impact of phosphorus exposure on the performance of flow through aftertreatment components such as Diesel Oxidation Catalysts (DOC) or Selective Catalytic Reduction (SCR) catalysts. The model is able to successfully determine the distribution of the phosphorus over the catalyst as a function of the aging history (temperature, flow rates, oil consumption rate, phosphorus content of the oil) as well as the component properties (diameter, length, cell density, wall thickness). The model then incorporates this information regarding the distribution of phosphorus over the catalyst surface to determine the impact of the phosphorus exposure on the overall catalytic activity. The model results were successfully validated using accelerated bench aging tests for the oxidation of hydrocarbons over DOC's and NH₃ oxidation and NOx reduction over SCR catalysts.