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Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

The dynamics and evolution of turbulent structures inside an engine-like geometry are investigated by means of Large Eddy Simulation. A simplified configuration consisting of a flat-top cylinder head with a fixed, axis-centered valve and low-speed piston has been simulated by the finite volume CFD code OpenFOAM®; the standard version of the software has been extended to include the compressible WALE subgrid-scale model, models for the generation of synthetic turbulence, some improvements to the mesh motion strategy and algorithms for LES data post-processing. In order to study both the initial transient and the quasi- steady operating conditions, ten complete engine cycles have been simulated. Phase and spatial averages have been performed over cycles three to ten in order to extract first and second moment of velocity; these quantities have then been used to validate the numerical procedure by comparison against experimental data.

A new electric powertrain and axle for light/medium trucks is presented. The indoor testing and the simulation of the dynamic behavior are performed. The powertrain and axle has been produced by Streparava and tested at the Laboratory for the Safety of Transport of the Politecnico di Milano. The tests were aimed at defining the multi-physics perfomance of the powertrain and axle (efficiency, acceleration and braking, temperature and NVH). The whole system for indoor tests was composed by the powertrain and axle (electric motor, driveline, suspensions, wheels) and by the test rig (drums, driveline and electric motor). The (driving) axle was positioned on a couple of drums, and the drums provided the proper torques to the wheels to reproduce acceleration and braking. Additionally a cleat fixed on one drum excited the vibration of the suspensions and allowed assessing NVH performance. The simulations were based on a special co-simulation between 1D-AMESIM and VIRTUAL.LAB.

In this paper, computation fluid dynamics (CFD) simulations are employed to describe the effect of flow parameters on the formation of soot and NOx in a heavy duty engine under low load and high load. The complexity of diesel combustion, specially when soot, NOx and other emissions are of interest, requires using a detailed chemical mechanism to have a correct estimation of temperature and species distribution. In this work, Multiple Representative Interactive Flamelets (MRIF) method is employed to describe the chemical reactions, ignition, flame propagation and emissions in the engine. A phenomenological model for soot formation, including soot nucleation, coagulation and oxidation with O2 and OH is incorporated into the flamelet combustion model. Different strategies for modelling NOx are chosen to take into account the longer time scale for NOx formation. The numerical results are compared with experimental data to show the validity of the model for the cases under study.

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.

Swirling flows are very dominant in applied technical problems, especially in IC engines, and their prediction requires rather sophisticated modeling. An adaptive low-pass filtering procedure for the modeled turbulent length and time scales is derived and applied to Menter' original k - ω SST turbulence model. The modeled length and time scales are compared to what can potentially be resolved by the computational grid and time step. If the modeled scales are larger than the resolvable scales, the resolvable scales will replace the modeled scales in the formulation of the eddy viscosity; therefore, the filtering technique helps the turbulence model to adapt in accordance with the mesh resolution and the scales to capture.

The flow field resulting from injecting a gas jet into a crossflow confined in a narrow square duct has been studied under steady regime using schlieren imaging and laser Doppler velocimetry (LDV). This transparent duct is intended to simulate the intake port of an internal combustion engine fueled by gaseous mixture, and the jet is issued from a round nozzle. The schlieren images show that the relative small size of the duct would confine the development of the transverse jet, and the interaction among jet and sidewalls strongly influences the mixing process between jet and crossflow. The mean velocity and turbulence fields have been studied in detail through LDV measurements, at both center plane and several cross sections. The well-known flow feature formed by a counter rotating vortex pair (CVP) has been observed, which starts to appear at the jet exit section and persists far downstream contributing to enhancing mixing process.

Wheel and wheelhouses contribute up to 20-30% of the aerodynamic drag of passenger cars. Simulating the flow field around wheels is challenging due to the complexity of the flow structures generated by tires and rims, wheel rotation, tire deformation and contact with the ground. High accuracy is usually obtained with transient simulations that treat rim rotation with the Sliding Mesh (SM) approach, which is also computationally expensive. Previous studies have confirmed that the application of a tangential velocity component to the rim surface is unphysical for open rims, while a Moving Reference Frame (MRF) is lacking accuracy and the averaged results depend on the initial spokes position. These methods do not consider the dynamic nature of the problem. This work proposes the use of the Actuator Line (AL) and Rotor Disk (RD) approaches as alternatives for simulating open rims with much lower computational cost.

The definition of a robust methodology to perform a full-cycle CFD simulation of IC engines requires as first step the availability of a reliable grid generation tool, which does not only have to guarantee a high quality mesh but also has to prove to be efficient in terms of required time. In this work the authors discuss a novel approach entirely based on the OpenFOAM technology, in which the available 3D grid generator was employed to automatically create meshes containing hexahedra and split-hexahedra from triangulated surface geometries in Stereolithography (STL) format. The possibility to introduce local refinements and boundary layers makes this tool suitable for IC engine simulations. Grids are sequentially generated at target crank angles which are automatically determined depending on user specified settings such as maximum mesh validity interval and quality parameters like non-orthogonality, skewness and aspect ratio.

The paper deals with the bifurcation analysis of a simple mathematical model describing an automobile running on an even surface. Bifurcation analysis is adopted as the proper procedure for an in-depth understanding of the stability of steady-state motion of cars (either cornering or running straight ahead). The aim of the paper is providing the fundamental information for inspiring further studies on vehicle dynamics with or without a human driver. The considered mechanical model of the car has two degrees of freedom, nonlinear tire characteristics are included. A simple driver model is introduced. Experimental validations of the model are produced. As a first step, bifurcation analysis is performed without driver (fixed control). Ten different combinations of front and rear tire characteristics (featuring understeer or oversteer automobiles) are considered. Steering angle and speed are varied. Many different dynamical behaviors of the model are found.

The reduction of the catalyst light-off time at the engine cold start represents a key factor for the pollutant emissions control from vehicles tested on homologation cycles and real drive conditions. The adoption of heating strategies to increase the temperature of the catalytic substrate in the early phase of the engine start is regarded as a promising solution. The present study focuses on the application of electrical heated catalyst (EHC) in an after-treatment line for a spark-ignition gasoline engine. The analysis is carried out by means of an advanced CFD framework, which includes the modeling of catalytic reactions in the substrates and accounts for the thermal evolution of all the components included in the after-treatment system.

The increasing diffusion of gasoline direct injection (GDI) engines requires a more detailed and reliable description of the phenomena occurring during the fuel injection process. As well known the thermal and fluid-dynamic conditions present in the combustion chamber greatly influence the air-fuel mixture process deriving from GDI injectors. GDI fuel sprays typically evolve in wide range of ambient pressure and temperatures depending on the engine load. In some particular injection conditions, when in-cylinder pressure is relatively low, flash evaporation might occur significantly affecting the fuel-air mixing process. In some other particular injection conditions spray impingement on the piston wall might occur, causing high unburned hydrocarbons and soot emissions, so currently representing one of the main drawbacks of GDI engines.

Predictive combustion models are useful tools towards the development of clean and efficient engines operating with alternative fuels. This work intends to validate two different combustion models on compression-ignition engines fueled with Dimethyl Ether. Both approaches give a detailed characterization of the combustion kinetics, but they substantially differ in how the interaction between fluid-dynamics and chemistry is treated. The first one is single-flamelet Representative Interactive Flamelet, which considers turbulence-kinetic interaction but cannot correctly describe the stabilization of the flame. The second, named Tabulated Well Mixed, correctly accounts for local flow and mixture conditions but does not consider interaction between turbulence and chemistry. An experimental campaign was carried out on a heavy-duty truck engine running on DME at a constant load considering trade-off of EGR and SOI.

A comprehensive model for sprays emerging from high pressure swirl injectors for GDI engine application has been developed. The primary and secondary atomization mechanism as well as the evaporation process both in standard and superheated conditions are taken into account. The spray modelling after the injection is based on the Liquid Instability Sheet Atomization (LISA) approach, modified to correctly predict the liquid sheet thickness at the breakup length. The effect of different values of the superheat degree on evaporation and impact on the spray distribution and fuel-air mixing is analyzed. Comparisons with experimental data show good agreements under atmospheric conditions and with different superheated degrees, while some discrepancies occur under higher ambient pressures.

In this work, the possibility to perform a cold-flow simulation as a way to improve the accuracy of the starting conditions for a combustion simulation is examined. Specifically, a dual-fuel marine engine running on methanol/diesel and natural gas/diesel fueling conditions is investigated. Dual-fuel engines can provide a short-term solution to cope with the more stringent emission legislations in the maritime sector. Both natural gas and methanol appear to be interesting alternative fuels that can be used as main fuel in these dual-fuel engines. Nevertheless, it is observed that combustion problems occur at part load using these alternative fuels. Therefore, different methods to increase the combustion efficiency at part load are investigated. Numerical simulations prove to be very suitable hereto, as they are an efficient way to study the effect of different parameters on the combustion characteristics.

NH₃/urea SCR is a very effective and widely used technology for the abatement of NOx from diesel exhaust. The SCR mechanism is well understood and the catalyst behavior can be predicted by mathematical models - as long as operation above the temperature limit for AdBlue® injection is considered. The behavior below this level is less understood. During the first seconds up to minutes after cold start, complete NOx abatement can be observed over an SCR catalyst in test bench experiments, together with a significant increase in temperature after the converter (ca. 100 K). In this work these effects have been investigated over a monolith Cu-zeolite SCR catalyst. Concentration step experiments varying NO, NO₂ and H₂O have been carried out in lab scale, starting from room temperature. Further, the interaction of C₃H₆ and CO with NOx over the SCR has been investigated.

In recent years, concerns for environmental pollution and oil price stimulated the demand for vehicles based on technologies alternative to traditional IC engines. Nowadays several carmakers include hybrid vehicles among their offer and first full electric vehicles appear on the market. Among the different layout of the electric power-train, four in-wheel motors appear to be one of the most attractive. Besides increasing the inner room, this architecture offers the interesting opportunity of easily and efficiently distribute the driving/braking torque on the four wheels. This characteristic can be exploited to generate a yaw moment (torque vectoring) able to increase lateral stability and to improve the handling of a vehicle. The present paper presents and compares two different torque vectoring control strategies for an electric vehicle with four in-wheel motors. Performances of the control strategies are evaluated by means of numerical simulations of open and closed loop maneuvers.

Roundabouts are intersections at which automated cars seem currently not performing sufficiently well. Actually, sometimes, they get stuck and the traffic flow is seriously reduced. To overcome this problem a V2N-N2V (vehicle-to-network-network-to-vehicle) communication scheme is proposed. Cars communicate via 5G with an edge computer. A cooperative machine-learning algorithm orchestrates the traffic. Automated cars are instructed to accelerate or decelerate with the triple aim of improving the traffic flow into the roundabout, keeping safety constraints, and providing comfort for passengers on board of automated vehicles. In the roundabout, both automated cars and human-driven cars run. The roundabout scenario has been simulated by SUMO. Additionally, the scenario has been reconstructed into a dynamic driving simulator, with a real human driver in a virtual reality environment. The aim was to check the human perception of traffic flow, driving safety and driving comfort.

Although the application of cylinder pressure sensors to gain insight into the combustion process is not a novel topic itself, the recent availability of inexpensive in-cylinder pressure sensors has again prompted an upcoming interest for the utilization of the cylinder pressure signal within engine control and monitoring. Besides the use of the in-cylinder pressure signal for combustion analysis and control the information can also be used to determine related quantities in the exhaust or intake manifold. Within this work two different methods to estimate the pressure inside the exhaust manifold are proposed and compared. In contrary to first principle based approaches, which may require time extensive parameterization, alternative data driven approaches were pursued. In the first method a Principle Component Analysis (PCA) is applied to extract the cylinder pressure information and combined with a polynomial model approach.

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.