On the Impact of Particulate Matter Distribution on Pressure Drop of Wall-Flow Particulate Filters

Evaluating the filtration efficiency of close-coupled catalyzed gasoline particulate filter (cGPF) over the WLTC and simulated RDE cycles

Gasoline particulate filter (GPF) is a cost-effective solution to particle number emissions from gasoline direct injection vehicles. Filtration efficiency, as a key parameter of GPF, was usually assessed at chassis level over regulatory drive cycles. However, the promulgation of real driving emission (RDE) requirements in the EU and Chinese regulations necessitates evaluations based on non-legislative cycles to guarantee the on-road emissions are compliant to regulatory requirements. In this research, two aggressive drive cycles, RTS95 at 23degC and modified RDE at 0degC, were complemented to the WLTC to evaluate the filtration efficiency of a catalyzed GPF (cGPF) in fresh conditions to obtain the so-called "worst-case" filtration efficiency. In the WLTC, RTS95, and simulated RDE tests, the filtration efficiency of the test cGPF was 51.1%, 41.3%, and 85.1% respectively. In the simulated RDE test, the test cGPF filtrated solid particles with a diameter above 23 nm and 10 nm at a similar efficiency. Increased filtration efficiency with heavier soot load could offset the relatively low filtration efficiency in cold-start and warm-up durations, hence the filtration efficiency for a clean cGPF showed higher sensitivity to cycle length over driving dynamics and testing temperature. In acceleration events with cGPF mounted, the particle diameter where number concentration peaked decreased as the engine warmed up. In deceleration events, bimodal and trimodal particle number size distributions with much lower concentrations were observed.

Machine Learning Applied to the NOx Prediction of Diesel Vehicle under Real Driving Cycle

Euro 6 standards impose stringent nitrogen oxide (NOx) emission limits on diesel cars. NOx emissions are significantly different between Euro 6 diesel cars and the previous standards in real-world driving. In this research, the NOx concentrations of Euro 6 diesel engines during real-world driving were studied considering various factors. Real driving emission (RDE) tests were conducted using vehicles equipped with portable emissions measurement systems. Urban, rural, and motorway test routes were utilized. Road environment, atmospheric, and after-treatment performance factors were collected in each case. An artificial neural network was used for evaluation using RDE test data and various statistical parameters. It was found that the proposed method predicted the pollutant emissions effectively. Lastly, the relative importance of each predictor was derived, and the NOx concentrations were analyzed. These approaches provide accurate emission information for an environmental effect evaluation that reflects more realistic road conditions.

Most Recent Advances in Diesel Engine Catalytic Soot Abatement: Structured Catalysts and Alternative Approaches

Diesel engine emissions are typically composed of several hundred chemical compounds, partly present in the gas phase and partly in solid phase as particles, the so-called particulate matter or soot. The morphology of the catalyst is an important characteristic of soot particles’ abatement, since a good contact between catalyst and soot is mandatory. For practical purposes, the active species should be supported as a film on the structured carrier, in order to allow simultaneous soot filtration and combustion. This review focuses on the most recent advances in the development of structured catalysts for diesel engine catalytic soot combustion, characterized by different active species and supports, as well as by different geometric configurations (monoliths, foams, ceramic papers, or wire mesh); the most important peculiar properties are highlighted and summarized. Moreover, a critical review of the most recent advances in modeling studies is also presented in this paper. In addition, some highlights on some of the most recent alternative approaches proposed for limiting the soot emissions from diesel engines have been given, delineating feasible alternatives to the classical strategies nowadays used.

Numerical Simulation of a Wall-Flow Particulate Filter Made of Biomorphic Silicon Carbide Able to Fit Different Fuel/Biofuel Inputs

To meet the increasingly strict emission limits imposed by regulations, internal combustion engines for transport applications require the urgent development of novel emission abatement systems. The introduction of biodiesel or other biofuels in the engine operation is considered to reduce greenhouse gas emissions. However, these alternative fuels can affect the performance of the post-combustion systems due to the variability they introduce in the exhaust particle distribution and their particular physical properties. Bioceramic materials made from vegetal waste are characterized by having an orthotropic hierarchical microstructure, which can be tailored in some way to optimize the filtration mechanisms as a function of the particle distribution of the combustion gases. Consequently, they can be good candidates to cope with the variability that new biofuel blends introduce in the engine operation. The objective of this work is to predict the filtration performance of a wall-flow particulate filter (DPF) made of biomorphic silicon carbide (bioSiC) with a systematic procedure that allows to eventually fit different fuel inputs. For this purpose; a well-validated DPF model available as commercial software has been chosen and adapted to the specific microstructural features of bioSiC. Fitting the specific filtration and permeability parameters of this biomaterial into the model; the filtration efficiency and pressure drop of the filter are predicted with sufficient accuracy during the loading test. The results obtained through this study show the potential of this novel DPF substrate; the material/microstructural design of which can be adapted through the selection of an optimum precursor.

Late Fuel Post-Injection Influence on the Dynamics and Efficiency of Wall-Flow Particulate Filters Regeneration

Late fuel post-injections are the most usual strategy to reach high exhaust temperature for the active regeneration of diesel particulate filters. However, it is important to optimise these strategies in order to mitigate their negative effect on the engine fuel consumption. This work aims at understanding the influence of the post-injection parameters, such as its start of injection and its fuel quantity, on the duration of the regeneration event and the fuel consumption along it. For this purpose, a set of computational models are employed to figure out in a holistic way the involved phenomena in the interaction between the engine and the exhaust gas aftertreatment system. Firstly, an engine model is implemented to evaluate the effect of the late fuel post-injection pattern on the gas properties at the exhaust aftertreatment system inlet in different steady-state operating conditions. These are selected to provide representative boundary conditions of the exhaust gas flow concerning dwell time, exhaust temperature and O 2 concentration. In this way, the results are later applied to the analysis of the diesel oxidation catalyst and wall-flow particulate filter responses. The dependence of the diesel particulate filter (DPF) inlet temperature is discussed based on the efficiency of each post-injection strategy to increase the exhaust gas temperature. Next, the influence on the dynamics of the regeneration of the post-injection parameters through the change in gas temperature and O 2 concentration is finally studied distinguishing the pre-heating, maximum reactivity and late soot oxidation stages as well as the required fuel consumption to complete the regeneration process.

Why the Development of Internal Combustion Engines Is Still Necessary to Fight against Global Climate Change from the Perspective of Transportation

Internal combustion engines (ICE) are the main propulsion systems in road transport [...]

Impact of Particulate Size During Deep Loading on DPF Management

Wall-flow particulate filters are a required emission control device to abate diesel emission in order to comply with current regulations. DPFs (diesel particulate filters) are characterized by high filtration efficiency—but in order to avoid deterioration of power and performance, they are required to cause low values of backpressure. The periodical oxidation of collected particle allows for the reestablishment of the ideal flow conditions. Studies highlighted that the regeneration event has an important impact on engine emission, since it is responsible for the emission of a large number of smaller particles. From these considerations, the importance of optimizing the DPF management for what concerns both filtration and regeneration mechanisms arises. The present paper focuses on the loading process of the filter. A filtration model was implemented, based on the ‘unit-collector’ and fluid-dynamic approaches, known as valid modelling techniques. The model was used to predict trapped mass and filter backpressure evolution with time during loading processes, in which soot particle sizes varied, with the aim to analyze how particulate size affects the filter pressure drop rise. A wall-flow filter was investigated, and the behavior of clean material was evaluated by a parametric analysis in which particle diameter varies in the filed 20–1000 nm, that is the typical range of soot sizes in diesel engine exhaust. The results demonstrate that soot size has a great influence on the initial deep bed loading process. Moreover, it defines the value from which the linear pressure drop shape during cake filtration starts, not only when the initial loaded is completed, but also each time the regeneration event is concluded. This outcome provides an important guideline to define the most appropriate strategy for the initial DPF loading in order to establish the regeneration event based on the estimation of trapped mass accounting for the filter backpressure and on the time interval between two successive regeneration.

Study on a New Gasoline Particulate Filter Structure Based on the Nested Cylinder and Diversion Channel Plug

Increasingly stringent emission regulations have imposed strict requirements on the particulate matter (PM) from gasoline direct injection (GDI) engines, and the gasoline particulate filters (GPFs) are considered one of the most promising devices for meeting these requirement. To reduce the flow resistance of the GPF, a type of nested cylinder and diversion channel plug (NC-DCP) GPF is designed. It is composed of nested foam metal cylinders and annular diversion channel plugs. The pressure drop and its influencing factors were theoretically studied. The results show that the structural parameters, such as the cylindrical layer spacing and the length-to-diameter ratio, and the pressure drop have trade-off relationships. Moreover, the filtration efficiency is analyzed, and the calculation formula is summarized. The internal flow field distribution and its influencing factors are discussed based on a 2-D axisymmetric simulation. The results show that the exhaust velocity affects the flow field uniformity but does not affect the flow field structure. The pressure drop gradually decreases as the number of nested layers increases, and the positive direction is beneficial to reduce the overall pressure drop. Under different velocities, there is an optimal length-to-diameter ratio to minimize the pressure drop, and the simicircular diversion plug greatly improves the flow uniformity index for the internal flow field of the filter element.

Computational Methodology for Knocking Combustion Analysis in Compression-Ignited Advanced Concepts

In the present work, a numerical methodology based on three-dimensional (3D) computational fluid dynamics (CFD) was developed to predict knock in a 2-Stroke engine operating with gasoline Partially Premixed Combustion (PPC) concept. Single-cycle Unsteady Reynolds-Averaged Navier Stokes (URANS) simulations using the renormalization group (RNG) k − ε model were performed in parallel while the initial conditions are accordingly perturbed in order to imitate the variability in the in-cylinder conditions due to engine operation. Results showed a good agreement between experiment and CFD simulation with respect to cycle-averaged and deviation of the ignition timing, combustion phasing, peak pressure magnitude and location. Moreover, the numerical method was also demonstrated to be capable of predicting knock features, such as maximum pressure rise rate and knock intensity, with good accuracy. Finally, the CFD solution allowed to give more insight about in-cylinder processes that lead to the knocking combustion and its subsequent effects.