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In this work a detailed model to simulate the transient behavior of catalytic converters is presented. The model is able to predict the unsteady and reacting flows in the exhaust ducts, by solving the system of conservation equations of mass, momentum, energy and transport of reacting chemical species. The en-gine and the intake system have not been included in the simulation, imposing the measured values of mass flow, gas temperature and chemical composition as a boundary condition at the inlet of the exhaust system. A detailed analysis of the diffusion stage triggering is proposed along with simplifications of the physics, finalized to the reduction of the calculation time. Submodels for water condensation and its following evaporation on the monolith surface have been taken into account as well as oxygen storage promoted by ceria oxides.

Ammonia/urea-SCR is a mature technology, applied worldwide for the control of NOx emissions in combustion exhausts from thermal power plants, cogeneration units, incinerators and stationary diesel engines and more recently also from mobile sources. However a greater DeNOx activity at low temperatures is desired in order to meet more and more restrictive legislations. In this paper we report transient and steady state data collected over commercial Fe-ZSM-5 and V₂O₅-WO₃/TiO₂ catalysts showing high NOx reduction efficiencies in the 200 - 350°C T-range when NO and ammonia react with nitrates, e.g., in the form of an aqueous solution of ammonium nitrate. Under such conditions a new reaction occurs, the so-called "Enhanced SCR" reaction, 2 NH₃ + 2 NO + NH₄NO₃ → 3 N₂ + 5 H₂O.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

The selective catalytic reduction has seen widespread adoption as the best technology to reduce the NOx emissions from internal combustion engines, particularly for Diesels. This technology uses ammonia as a reducing agent, which is obtained injecting an ammonia carrier into the exhaust gas stream. The dosing of the ammonia carrier, usually AdBlue, is the major concern during the design and engine calibration phases, since the interaction between the injected liquid and the components of the exhaust system can lead to the undesired formation of solid deposits. To avoid this, the thermal and kinematic interaction between the spray and the components of the after treatment system (ATS) must be modeled accurately. In this work, the authors developed a Conjugate Heat Transfer (CHT) framework to model the kinetic and thermal interaction among the spray, the eventual liquid layer and the pipe walls.

The injection process of urea-water solution (AdBlue) determines initial conditions for reactions and catalysis and is fundamentally responsible for optimal operation of selective catalytic reduction (SCR) systems. The spray characteristics of four, commercially available, injectors (one air-assisted and three pressure-driven with different nozzle-hole configurations) are investigated with non-intrusive measuring techniques. Injection occurred in the crossflow of a channel blowing preheated air in an exhaust duct similar configuration. The effect of several gas temperatures and flows on the spray propagation and entrainment has been extensively studied by shadow imaging. Shadow images, in addition, show that the spray of the pressure-driven injectors is only marginally affected by the gas crossflow. In contrast, the air assisted spray is strongly deflected by the gas, the effect increasing with increasing gas flow.

An aqueous urea solution is used as the source of ammonia for selective catalytic reduction (SCR) of NOx to reduce the emissions of NOx in the exhaust of diesel vehicles. However, the decomposition of urea into ammonia is not always complete, resulting in solid urea deposit formation in the decomposition tube or on the SCR catalyst. These solid deposits can impede the flow of the exhaust gases (and uniformity of NH3 supply) and reduce SCR catalyst performance over time. To minimize the formation of urea deposit and to meet EPA NOx emission regulations, it is important to understand the chemistry of formation or removal of the deposit in the decomposition tube and SCR catalyst. In this report, IR spectroscopy, UV-visible spectroscopy, thermogravimetric analysis and elemental analysis have been used to determine the chemical composition of the solid urea deposits formed by the thermal decomposition of urea.

Metallic foams or sponges are materials with a cell structure suitable for many industrial applications, such as reformers, heat catalytic converters, etc. The success of these materials is due to the combination of various characteristics such as mechanical strength, low density, high specific surface, good thermal exchange properties, low flow resistance and sound absorption. Different materials and manufacturing processes produce different type of structure and properties for various applications. In this work a genetic algorithm has been developed and applied to support the design of catalytic devices. In particular, two substrates were considered, namely the traditional honeycomb and an alternative open-cell foam type. CFD simulations of pressure losses and literature based correlations for the heat and mass transfer were used to support the genetic algorithm in finding the best compromise between flow resistance and pollutant abatement.

The paper deals with the design and manufacturing of a McPherson suspension arm made from short glass fiber reinforced polyamide (PA66). The design of the arm and the design of the molds have been made jointly. According to Industry 4.0 paradigms, a full digitalization of both the product and process has been performed. Since the mechanical behavior of the suspension arm strongly depends on constraints which are difficult to be modelled, a simpler structure with well-defined mechanical constraints has been developed. By means of such simple structure, the model for the behavior of the material has been validated. Since the suspension arm is a hybrid structure, the associated simple structure is hybrid as well, featuring a metal sheet with over-molded polymer. The issues referring to material flow, material to material contact, weld lines, fatigue strength, high and low temperature behavior, creep, dynamic strength have been investigated on the simple structure.

Selective Catalytic Reduction (SCR) systems are nowadays widely applied for the reduction of NOx emitted from Diesel engines. The typical process is based on the injection of aqueous urea in the exhaust gases before the SCR catalyst, which determines the production of the ammonia needed for the catalytic reduction of NOx. However, this technology is affected by two main limitations: a) the evaporation of the urea water solution (UWS) requires a sufficiently high temperature of the exhaust gases and b) the formation of solid deposits during the UWS evaporation is a frequent phenomenon which compromise the correct operation of the system. In this context, to overcome these issues, a technology based on the injection of gaseous ammonia has been recently proposed: in this case, ammonia is stored at the solid state in a cartridge containing a Strontium Chloride salt and it is desorbed by means of electrical heating.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.

Transient and steady-state kinetic data are herein presented to analyze the inhibiting effect of ammonia on the NH₃-SCR of NO at low temperatures over a Fe-zeolite commercial catalyst for vehicles. It is shown that in SCR converter models a rate expression accounting for NH₃ inhibition of the Standard SCR reaction is needed in order to predict the specific dynamics observed both in lab-scale and in engine test bench runs upon switching on and off the ammonia feed. Two redox, dual site kinetic models are developed which ascribe such inhibition to the spill-over of ammonia from its adsorption sites, associated with the zeolite, to the redox sites, associated with the Fe promoter. Better agreement both with lab-scale intrinsic kinetic runs and with engine test-bench data, particularly during transients associated with dosing of ammonia to the SCR catalyst, is obtained assuming slow migration of NH₃ between the two sites.

The present paper investigates possible enhancement of ESP performance associated with the use of smart tires. In particular a novel control logic based on a direct feedback on the longitudinal forces developed by the four tires is considered. The control logic was developed using a simulation tool including a 14 dofs vehicle model and a smart tires emulator. Performance of the control strategy was evaluated in a series of handling maneuvers. The same maneuvers were performed on a HiL test bench interfacing the same vehicle model with a production ESP ECU. Results of the two logics were analyzed and compared.

Rear Window Buffeting (RWB) is the low-frequency, high amplitude, sound that occurs in many 4-door vehicles when driven 30-70 mph with one rear window lowered. The goal of this paper is to demonstrate that the mechanisms of RWB are similar to that of sun roof buffeting and to describe the results of several actions suspected in contributing to the severity of RWB. Finally, the results of several experiments are discussed that may lend insight into ways to reduce the severity of this event. A detailed examination of the side airflow patterns of a small Sport Utility Vehicle (SUV) shows these criteria exist on a small SUV, and experiments to modify the SUV airflow pattern to reduce RWB are performed with varying degrees of success. Based on the results of these experiments, design actions are recommended that may result in the reduction of RWB.

Engineering education at the University level is enhanced by competition-based projects. The SAE Clean Snowmobile Challenge is a prime example of how competition-based engineering education benefits the small engines industry and improves the engineering talent pool of the nation in general. For the past several decades, SAE has encouraged young engineers to compete in designing off road vehicles (Baja SAE ®), small race cars (Formula SAE ®), remote control airplanes (Aero Design ®), high mileage vehicles (Supermileage ®) and robots (Walking Robot ®). Now a new competition, the SAE Clean Snowmobile Challenge ™ (CSC), based on designing a cleaner and quieter snowmobile has led to a new path for young engineers to explore the challenges of designing engines that emit less pollution and noise. The paper will summarize the results of the most recent Clean Snowmobile Challenge 2006 and document the successes of the past seven years of the Challenge.

The sustainability of Martian outposts development is strongly based on the capability of achieving a high level of autonomy both in terms of operations management and of resources availability. In situ production of consumables is a key point to allow humans to work and live on Mars avoiding or limiting the need for re-supplies of materials from Earth. Required consumables can be produced in situ exploiting the locally available resources, but also by means of green-houses and waste recycle systems. Dedicated robotic missions for in situ demonstration of this type of technologies are a fundamental step of the Martian In Situ Resources Utilization (ISRU) development roadmap. This paper is focused on the extraction of oxygen and fuels (e.g. methane) from the Martian atmosphere, and presents a feasibility study for a small technological demonstration plant.

Model-based control strategies are important for meeting the dual objective of maximizing NOx reduction and minimizing NH3 slip in urea-SCR catalysts. To be implementable on the vehicle, the models should capture the essential behavior of the system, while not being computationally intensive. This paper discusses the adequacy of two different reduced order SCR catalyst models and compares their performance with a higher order model. The higher order model assumes that the catalyst has both diffusion and reaction kinetics, whereas the reduced order models contain only reaction kinetics. After describing each model, its parameter identification and model validation based on experiments on a Navistar I6 7.6L engine are presented. The adequacy of reduced order models is demonstrated by comparing the NO, NO2 and NH3 concentrations predicted by the models to their concentrations from the test data.

Experimental studies have shown that knitted wiremesh mixers reduce the formation of solid deposits and improve ammonia homogenization in automotive SCR systems. However, their implementation in CFD models remains a major challenge due to the complex WM geometry. It was the aim of the current study to investigate droplet WM interaction. Essential processes, such as secondary droplet generation, wall film formation, and heat exchange, were analyzed in detail and a numerical model was set up. A box with heat resisting glass was used to study urea-water solution spray impingement on a WM under a wide range of operating conditions. High speed videography was used to identify the impingement regimes. Infrared thermography was applied to investigate WM cooling. In order to determine the impact of the WM on the spray characteristics, the droplet spectrum was measured both upstream and downstream of the WM using the laser diffraction method.

The application of liquid aqueous Urea Solution (AUS) as reductant in SCR exhaust after-treatment systems is now a commonly accepted industry standard. Unfortunately, less acceptable are the associated difficulties caused by incomplete decomposition of the liquid, resulting in solid deposits which accumulate in the exhaust pipe downstream of the dosing components. The correct prediction of the spray pattern and, therefore, the spray impact on the walls is a key feature for the system optimization. A mechanical patternator, designed on the basis of CFD performance assessment, involving a Lagrangian representation of the dispersed liquid fully coupled with a 3D Eulerian description of the carrier phase, has been built and used to measure the spray mass distribution.

Premixed combustion modes in compression ignition engines are studied as a promising solution to meet fuel economy and increasingly stringent emissions regulations. Nevertheless, PCCI combustion systems are not yet consolidated enough for practical applications. The high complexity of such combustion systems in terms of both air-fuel charge preparation and combustion process control requires the employment of robust and reliable numerical tools to provide adequate comprehension of the phenomena. Object of this work is the development and validation of suitable models to evaluate the effects of charge premixing levels in diesel combustion. This activity was performed using the Lib-ICE code, which is a set of applications and libraries for IC engine simulations developed using the OpenFOAM® technology.

This paper provides a review on state-of-art modern cooling systems employed for thermal cooling of electric motors for vehicle applications. In recent years, the pursue of a more sustainable and ecofriendly mobility has pushed the research towards the development of electric vehicle powertrain systems. Besides the evident advantages of the adoption of electric traction systems in terms of pollution and efficiency, the need of an effective cooling system for the electric machine components gained more and more importance in order to maintain high efficiency and ensure high durability. In fact, it is known that high temperatures can be harmful for the electric motor: besides the evident damages for mechanical parts, the influence on the permanent magnet properties is not negligible [1] [2]. In this fast-evolving environment, different solutions for the thermal problem have been researched and adopted, each one with its own pros and cons.