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Worldwide regulations concerning noise emissions of road vehicles are constantly demanding further reductions of acoustic emissions, which are considered a major environmental health concern in several countries. Among the different sources contributing to noise generation in vehicles equipped with internal combustion engines, exhaust flow noise is one of the most significant, being generated by turbulence development in the exhaust gases, and robust and reliable numerical methodologies for its prediction in early design phases are currently still needed. To this extent, Computational Aero-Acoustics (CAA) can be considered a valuable approach to characterize the physical mechanisms leading to flow noise generation and its propagation, and it could therefore be used to support exhaust system development prior to the execution of experimental testing campaigns.

The turbulent flow field inside the cylinder plays a major role in spark ignition (SI) engines. Multiple phenomena that occur during the high pressure part of the engine cycle, such as early flame kernel development, flame propagation and gas-to-wall heat transfer, are influenced by in-cylinder turbulence. Turbulence inside the cylinder is primarily generated via high shear flows that occur during the intake process, via high velocity injection sprays and by the destruction of macro-scale motions produced by tumbling and/or swirling structures close to top dead center (TDC) . Understanding such complex flow phenomena typically requires detailed 3D-CFD simulations. Such calculations are computationally very expensive and are typically carried out for a limited number of operating conditions. On the other hand, quasi-dimensional simulations, which provide a limited description of the in-cylinder processes, are computationally inexpensive.

Natural gas is a promising alternative fuel for internal combustion engine application due to its low carbon content and high knock resistance. Performance of natural gas engines is further improved if direct injection, high turbocharger boost level, and variable valve actuation (VVA) are adopted. Also, relevant efficiency benefits can be obtained through downsizing. However, mixture quality resulting from direct gas injection has proven to be problematic. This work aims at developing a mono-fuel small-displacement turbocharged compressed natural gas engine with side-mounted direct injector and advanced VVA system. An injector configuration was designed in order to enhance the overall engine tumble and thus overcome low penetration.

The fuel injection plays a crucial role in determining the mixture formation process in Gasoline Direct Injection (GDI) engines. Pollutant emissions, and soot emissions in particular, as well as phenomena affecting engine reliability, such as oil dilution and injector coking, are deeply influenced by the injection system features, such as injector geometric characteristics (such as injector type, injector position and targeting within the combustion chamber) and operating characteristics (such as injection pressure, injection phasing, etc.). In this paper, a new CFD methodology is presented, allowing a preliminary assessment of the mixture formation quality in terms of expected soot emissions, oil dilution and injector coking risks for different injection systems (such as for instance multihole or swirl injectors) and different injection strategies, from the early stages of a new engine design.

Development trends in modern common rail fuel injection systems (FIS) show dramatically increasing capabilities in terms of optimization of the fuel injection strategy through a constantly increasing number of injection events per engine cycle as well as through the modulation and shaping of the injection rate. In order to fully exploit the potential of the abovementioned fuel injection strategy optimization, numerical simulation can play a fundamental role by allowing the creation of a kind of a virtual test rig, where the input is the fuel injection rate and the optimization targets are the combustion outputs, such as the burn rate, the pollutant emissions, and the combustion noise (CN).

The unsteady flow effects in two different close coupled catalytic converters were investigated in order to achieve a better understanding of the steady state experimental tests which are usually performed to evaluate a flow distribution. Firstly the validity of a CFD model was achieved through a comparison of some steady state simulations with the results of HWA experimental measurements. Several different formulations of the uniformity index, that were found in literature, were then compared, trying to highlight the strengths and shortcomings of each one. Further information was derived from a comparison of the two catalysts that were tested to achieve a general methodology that would be useful for future analysis. Finally, a new approach to evaluate the flow distribution using a steady state analysis was proposed by comparing the results of a transient simulation that was obtained for a whole engine cycle.

Computational Fluid Dynamics is a powerful instrument for PEM fuel cell systems development, testing and optimization. Considering the complication due to the multiple physical phenomena involved in the cell's operations, a good understanding of the micro-scale fluidic behavior in boundary layers is recommended: pressure drop along the reactants gas channels and the cooling channels has a sensible effect on parasite load in fuel cell systems (i.e. the power absorbed by the pump supplying the gases), as well as an important role in thermal transport. A correct thermal and fluid dynamic boundary layer prediction on the channel walls and the other contact surface with porous layers requires usually a dense finite element volumes discretization near wall, especially if laminar flows occur: therefore, the boundary layer computational cost tends to be the major one.

One of the major issues coming out from low temperature fuel cells concerns the production of water vapor as a chemical reaction (between hydrogen and oxygen) by-product and its consequent condensation (at certain operating conditions), determining the presence of an amount of liquid water affecting the performance of the fuel cell stack: the production and the quantity of liquid water are strictly influenced by boundaries and power output conditions. Starting from this point, this work focuses on collecting all the required information available in literature and defining a suitable CFD model able to predict the production of liquid water within the fuel cell, while at the same time localizing it and determining the consequences on the PEM cell performances.

A fuel-cell-based system's performance is mainly identified in the overall efficiency, strongly depending on the amount of power losses due to auxiliary devices to supply. In such a situation, everything that causes either a decrease of the available power output or an increment of auxiliary losses would determine a sensible overall efficiency reduction.

JUNO is an urban concept vehicle (developed at the Politecnico of Torino), equipped by an ethanol combustion engine, designed to obtain low consumptions and reduced environmental impact. For these goals the main requirements that were considered during the designing process were mass reduction and aerodynamic optimization, at first on the shape of the car body and then, thanks to add-on devices. JUNO’s aerodynamic development follows a defined workflow: geometry definition and modelling, CFD simulations and analysis, and finally geometry changes and CFD new verification. In this paper the results of the CFD simulations (using STARCCM+ and RANS k-ε) with a corresponding 1/1 scale wind tunnel tests made using the real vehicle. Particularly, the results in term of: total drag coefficient (Cx), total lift coefficient (Cz), the total pressure in the side and rear analyzing twenty different aerodynamics configurations made up of different combination of some aerodynamics add-on devices.

In this work, a methodology for building and calibrating the kinetic scheme for the 1D CFD model of a zone-coated automotive Diesel Oxidation Catalyst (DOC) by means of a Genetic Algorithm (GA) approach is presented. The methodology consists of a preliminary experimental activity followed by a modelling, optimization and validation process. The tested aftertreatment component presents zone coating, with the front brick side covered with Zeolites in order to ensure hydrocarbons trapping at low temperature, and Platinum Group Metal (PGM), while the rear brick side presents an alumina washcoat with a different PGM loading. Reactor scale samples representative of each coating zone were tested on a Synthetic Gas Bench (SGB), to fully characterize the component’s behavior in terms of Light-off and hydrocarbons (HC) storage for a wide range of inlet feed compositions and temperatures, representative of engine-out conditions.

The clutch is that mechanical part located in an internal combustion engine vehicle which allows the torque transmission from the shaft to the wheels, permitting at the same time gear shifting and supporting engine revolutions while the car is idling. This component exploits friction as working principle, therefore heat generation is in its own nature. The comprehension of all the critical issues related to thermal emission, and also of the principal physical parameters driving the phenomena are a must in design phases. The subject of this paper is the elaboration of an accurate, but also easy to use and easily replicable, methodology to simulate thermal behavior of a clutch operating inside its usual environment. The present methodology allows to prevent corrective actions in the last phase of the projects (real testing), such as changes in gear ratios, that likely worsen CO2 emissions, permitting to achieve the wished thermal performance of the clutch avoiding late changes.

XAM is a two-seat city vehicle prototype developed at the Politecnico di Torino, equipped with a hybrid propulsion system to obtain low consumptions and reduced environmental impact. The design of this vehicle was guided by the requirements of weight reduction and aerodynamic optimization of the body, aimed at obtaining a reduction of resistance while guarantying roominess. The basic shape of the vehicle corresponding to the requirements of style, ergonomics and structure were deeply studied through CFD simulation in order to assess its aerodynamic performance (considering the vehicle as a whole or the influence of the various details and of their changes separately). The most critical areas of the body (underfloor, tail, spoiler, mirrors, A-pillar) were analyzed creating dedicated refinement volumes.

Nautilus S.p.A. and the Polytechnic of Turin, in cooperation with Blue Engineering, have developed a very versatile product, the ELETTRA Twin Flyers [6] (ETF), which consists in a very innovative remotely-piloted airship equipped with high precision sensors and communication devices. This multipurpose platform is particularly suitable for border and maritime surveillance missions and for telecommunication, both in military and civil area. To assess the actual maneuver capabilities of the airship [14], a prototype of reduced size and complexity has been assembled [16]. Before the flight tests a further assessment on the flight simulator is needed, because the first version of the software is tuned on the full scale prototype. Steady state performance and static stability of the demonstrator have been evaluated with CFD analysis.

Fuel cells are considered one of the promising technologies as possible replacement of Internal Combustion Engine (ICE) for the transportation sector due to their high efficiency, ultra-low (or zero) emissions and for the higher drive range. The Membrane Electrode Assembly (MEA) is what mainly influences the Fuel Cell FC performance, durability, and cost. In PEMFC the proton conductivity of the membrane is a function of the humidification level of the FC membrane, hence the importance of keeping the membrane properly humidified to achieve the best possible fuel cell performance. To have the optimal water content inside the fuel cell’s membrane several strategies could be adopted, dealing with the use of external device (such as membrane humidifier) or to adopt an optimal set of parameters (gas flow rate and temperature for example) to use the water produced at fuel cell cathode as humidity source. The aim of this paper is to study the behavior of a FC vehicle humidification system.

The ongoing global demand for greater energy efficiency plays an essential role in the automotive industry, as the focus is moving from ICEs to hybrid (HEVs) and electric (EVs) vehicles. New virtual methodologies are necessary to reduce the development effort of these technologies. In this context, the thermal management of the vehicle high voltage battery pack is becoming increasingly important, with significant impact on the vehicle’s range in different environmental scenarios. In this paper, an advanced method is proposed to compute 3D temperature distribution of the cells of a high voltage battery pack for Plug-in Hybrid (PHEV) or full electric (EV) applications. The thermal FE model of a complete PHEV vehicle was integrated with an electrical NTG equivalent circuit model of the HV battery to compute the heat loads of the cells.

Automotive manufacturers are facing stronger and stronger pressure to optimize all aspects related to fuel consumption of cars, and aerodynamic drag makes no exception, due to increasing government enforcing rules for the reduction of the emissions and the increasing influence of aerodynamic performance on fuel consumption with WLTC and RDE driving cycles. Nowadays, CFD simulation is a common tool across automotive industries for the assessment and the optimization of vehicle resistance in the design phase. The full power of these numerical methods of studying many design variants in advance of experimental testing, however, can be fully exploited when coupled with optimization techniques, always keeping into account constraints and aesthetical demands. On the other hand, a massive use of CFD optimization can lead to unaffordable computational efforts or a limitation of the design exploration space.

Battery Electric Vehicles (BEVs) and Hybrid Electric Vehicles (HEVs) are becoming relevant in the transportation sector, and it is therefore of utmost importance to find a solution to allow batteries to work safely and in a correct temperature range in which performance degradation and/or thermal runaway do not occur. For this purpose, a Battery Thermal Management System (BTMS) is required to ensure the correct operation of the battery pack. The design and control of an efficient BTMS is a complex task, in which multiple technical fields are involved. The paper mainly focuses on the thermal problems affecting the BTMS and sets two main goals: 1) to provide a comparison of two possible BTMS solutions, analyzing constraints and thermal performance for the design task; 2) to present a battery thermal 1D model able to describe the battery module behavior in real-time application to be implemented in a BMS control.

Polymer electrolyte membrane (PEM) fuel cells will play a crucial role in the decarbonization of the transport sector, in particular for heavy duty applications. However, performance and durability of PEMFC stacks is still a concern especially when operated under high power density conditions, as required in order to improve the compactness and to reduce the cost of the system. In this context, the optimization of the geometry of hydrogen and air distributors represents a key factor to improve the distribution of the reactants on the active surface, in order to guarantee a proper water management and avoiding membrane dehydration.

Compression ignition engine-based transportation is nowadays looking for cleaner combustion solutions. Among them, ducted fuel injection (DFI) is emerging as a cutting-edge technology due to its potential to drastically curtail engine-out soot emissions. Although the DFI capability to abate soot formation has been demonstrated both in constant-volume and optical engine conditions, its optimization and understanding is still needed for its exploitation on series production engines. For this purpose, computational fluid dynamics (CFD) coupled with low-cost turbulence models, like RANS, can be a powerful tool, especially in the industrial context. However, it is often challenging to obtain reliable RANS-based CFD simulations, especially due to the high dependence of the various state-of-the-art turbulence models on the case study.