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By analyzing the dynamic distortion in all body closure openings in a complete vehicle, a better understanding of the body characteristics can be achieved compared to traditional static load cases such as static torsional body stiffness. This is particularly relevant for non-traditional vehicle layouts and electric vehicle architectures. The body response is measured with the so-called Multi Stethoscope (MSS) when driving a vehicle on a rough pavé road (cobble stone). The MSS is measuring the distortion in each opening in two diagonals. During the virtual development, the distortion is described by the relative displacement in diagonal direction in time domain using a modal transient analysis. The results are shown as Opening Distortion Fingerprint ODF and used as assessment criteria within Solidity and Perceived Quality. By applying the Principal Component Analysis (PCA) on the time history of the distortion, a Dominant Distortion Pattern (DDP) can be identified.

Given the growing interest in improving the efficiency of the bus fleet in public transportation systems, this paper presents an analysis of the energy consumption of a battery electric bus. During the experimental campaign, a battery electric bus was loaded using sand payloads to simulate the passenger load on board and followed another bus during regular service. Data related to the energy consumed by various bus utilities were published on the vehicle’s CAN network using the FMS standard and sampled at a frequency of 1 Hz. The collected experimental data were initially analyzed on a daily basis and then on a per-route basis. The results reveal the breakdown of energy consumption among various utilities over the course of each day of the experiment, highlighting those responsible for the highest energy consumption.

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.

The employment of hydrogen as energy carrier for transportation sector represents a significant challenge for powertrains. Spark-ignition (SI) engines are feasible and low-cost devices to convert the hydrogen chemical energy into mechanical work. However, significant efforts are needed to successfully retrofit the available configurations. The computational fluid dynamics (CFD) modelling represents a useful tool to support experiments, clarifying the impact of the engine characteristics on both the mixture preparation and the combustion development. In this work, a CFD investigation is carried out on typical light-duty SI engine configurations, exploring the two main strategies of hydrogen addition: port fuel injection (PFI) and direct injection (DI). The purpose is to assess the behaviour of widely-used numerical models and methodologies when hydrogen is employed instead of traditional carbon-based fuels.

Turbulent Jet Ignition (TJI) represents one of the most effective solution to improve engine efficiency and to reduce fuel consumption and pollutants emission. Even if active prechambers allow a precise control of the air-fuel ratio close to the spark plug and the ignition of ultra-lean mixtures in the main chamber, passive prechambers represent a more attractive solution especially for passenger cars thanks to their simpler and cheaper configuration, which is easier to integrate into existing engines. The main challenge of passive prechambers is to find a geometry that allows to use TJI in the whole engine map, especially in the low load/speed region, without the use of a second sparkplug in the main chamber. To this end, this works reports a CFD study coupled with an experimental investigation to overcome this limitation.

The demand of game-changing technologies to improve efficiency and abate emissions of heavy-duty trucks and off-road vehicles promoted the development of novel engine concepts. The Recuperated Split-Cycle (R-SC) engine allows to recover the exhaust gases energy into the air intake by separating the compression and combustion stages into two different but connected cylinders: the compressor and expander, respectively. The result is a potential increase of the engine thermal efficiency. Accordingly, the 3D-computational fluid dynamics (CFD) modelling of the gas exchange process and the combustion evolution inside the expander becomes essential to control and optimize the R-SC engine concept. This work aims to address the most challenging numerical aspects encountered in a 3D numerical simulation of an R-SC engine.

The rising environmental awareness has led to a growing interest in electric and lightweight vehicles. Four-wheeled Ultra-Efficient Lightweight Vehicles (UELVs) have the potential to improve the quality of urban life, reduce environmental impact and make efficient use of land. However, the safety of these vehicles in terms of dynamic behaviour needs to be better understood. This paper aims to provide a quantitative assessment of the handling behaviour of UELVs. An analytical single-track model and a numerical simulation by VI-CarRealTime are analysed to evaluate the dynamic performance of a UELV compared to a city car. This analysis shows that the lightweight vehicle has a higher readiness (i.e. lower reaction time to yaw rate) for step steering and lower steering effort (i.e. higher steady-state value). Experimental analysis through real-time driving sessions on the Dynamic Driving Simulator assesses vehicle responses and subjective perception for different manoeuvres.

Wind turbines in cold climates are likely to suffer from icing events, deteriorating the aerodynamic performances of the blades and decreasing their power output. Continuous ice accretion causes an increase in the ice mass and, consequently, in the centrifugal force to which the ice shape is subjected. This can result in the shedding of chunks of ice, which can jeopardize the aeroelastic properties of the blade and, most importantly, the safety of the surrounding people and of the wind turbine structure itself. In this work, ice shedding analysis is performed on a quasi-3D, multi-step ice geometry accreted on the NREL 5MW reference wind turbine. A preliminary investigation is performed by including the presence of an ice protection system to decrease the adhesion surface of the ice on the blade. A reference test case with a simple geometry is used as verification for the correct implementation of the procedure.

This work presents a comprehensive numerical model for ice accretion and Ice Protection System (IPS) simulation over a 2D component, such as an airfoil. The model is based on the Myers model for ice accretion and extended to include the possibility of a heated substratum. Six different icing conditions that can occur during in-flight ice accretion with an Electro-Thermal Ice Protection System (ETIPS) activated are identified. Each condition presents one or more layers with a different water phase. Depending on the heat fluxes, there could be only liquid water, ice, or a combination of both on the substratum. The possible layers are the ice layer on the substratum, the running liquid film over ice or substratum, and the static liquid film between ice and substratum caused by ice melting. The last layer, which is always present, is the substratum. The physical model that describes the evolution of these layers is based on the Stefan problem. For each layer, one heat equation is solved.

This paper presents a novel fully-automatic remeshing procedure, based on the level-set method and Delaunay triangulation, to model three-dimensional boundary problems and generate a new conformal body-fitted mesh. The proposed methodology is applied to long-term in-flight ice accretion, which is characterized by the formation of extremely irregular ice shapes. Since ice accretion is coupled with the aerodynamic flow field, a multi-step procedure is implemented. The total icing exposure time is subdivided into smaller time steps, and at each time step a three-dimensional body-fitted mesh, suitable for the computation of the aerodynamic flow field around the updated geometry, is generated automatically. The methodology proposed can effectively deal with front intersections, as shown with a manufactured example.

This study examines the impact of slip in aero-thermal conditions of supercooled large droplets (SLD) produced in an Icing Wind Tunnel (IWT) on the ice accretion characteristics. The study identifies potential biases in the SLD model development based on IWT data and numerical predictions that assume the SLD to be in aerothermal equilibrium with the IWT airflow. To obtain realistic temperature and velocity data for each droplet size class in the test section of the Braunschweig Icing Wind Tunnel (BIWT), a Lagrangian droplet tracking solver was used within a Monte Carlo framework. Results showed that SLDs experience considerable slips in velocity and temperature due to their higher inertia and short residence time in the Braunschweig IWT. Large droplets were found to be warmer and slower than the flow in the test section, with larger droplets experiencing larger aerothermal slips.

We present a framework for the robust optimization of the heat flux distribution for an anti-ice electro-thermal ice protection system (AI-ETIPS) and iced airfoil performance analysis under uncertain conditions. The considered uncertainty regards a lack of knowledge concerning the characteristics of the cloud i.e. the liquid water content and the median volume diameter of water droplets, and the accuracy of measuring devices i.e., the static temperature probe, uncertain parameters are modeled as uniform random variables. A forward uncertainty propagation analysis is carried out using a Monte Carlo approach. The optimization framework relies on a gradient-free algorithm (Mesh Adaptive Direct Search) and three different problem formulations are considered in this work. Two bi-objective deterministic optimizations aim to minimize power consumption and either minimize ice formations or the iced airfoil drag coefficient.

Multi-purpose agricultural tractors are vehicles that are usually used in rough paths and on off-road situations characterized by strong slope variations. The main feature of this kind of vehicles is the stability in working conditions to avoid overturning while it is on duty. This characteristic is given by the interaction between the suspension system and the vehicle frame. Due to the limited size of this kind of vehicle, the stability feature could be given by chassis deformation or using a two-piece frame connected by a spherical joint. This paper presents the validation of a numerical lumped-parameters model able to reproduce the vertical dynamics of a multi-purpose tractor featured by a yielding chassis. The unknown model parameters have been estimated firstly with static tests to study the vertical tire and suspension stiffnesses. The dynamic tests using a four-post-test rig have been performed to tune the unknown dynamic parameters.

Since vehicles are comprised of thousands of components, it is essential to reduce the Life Cycle Inventory (LCI) modelling workload. This study aims to compare different LCI modeling workload-reducing scenarios to provide a trade-off between the workload efforts and result accuracy. To achieve the optimal balance between computational effort and data specification requirements, the driver seat is used as a case study, instead of the entire vehicle. When all the components of a conventional light-duty commercial vehicle are sorted by mass descending order, seats are among the first five. In addition, unlike the other components, seats are comprised of metals as well as a wide range of plastics and textiles, making them a representative test case for a general problem formulation. In this way, methodology and outcomes can be reasonably extended to the entire vehicle.

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 tightening trend of regulations on the levels of admitted pollutant emissions has given a great spur to the research work in the field of combustion and after-treatment devices. Despite the improvements that can be applied to the development of the combustion process, pollutant emissions cannot be reduced to zero; for this reason, the aftertreatment system will become a key component in the path to achieving near-zero emission levels. This study focuses on the numerical analysis and optimization of different metallic substrates, specifically developed for three-way catalyst (TWC) and Diesel oxidation catalyst (DOC) applications, to improve their thermal efficiency by reducing radial thermal losses through the outer mantle. The optimization process relies on computational fluid dynamics (CFD) simulations supported by experimental measurements to validate the numerical models carried out under uncoated conditions, where chemical reactions do not occur.

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.

Ducted Fuel Injection (DFI) has the potential to reduce soot emissions in Diesel engines thanks to the enhanced mixing rate resulting from the liquid fuel flow through a small cylindrical pipe located at a certain distance from the nozzle injector hole. A consolidated set of experiments in constant-volume vessel and engine allowed to understand the effects of ambient conditions, duct geometry and shape on fuel-air mixing, combustion and soot formation. However, implementation of this promising technology in compression-ignition engines requires predictive numerical models that can properly support the design of combustion systems in a wide range of operating conditions. This work presents a computational methodology to predict fuel-air mixing and combustion with ducted fuel injection. Attention is mainly focused on turbulence and combustion modelling.

In the last few years, the effect of diabatic test conditions on compressor performance maps has been widely investigated, leading some Authors to propose different correction models. The accuracy of turbocharger performance map constitute the basis for the tuning and validation of a numerical method, usually adopted for the prediction of engine-turbocharger matching. Actually, it is common practice in automotive applications to use simulation codes, which can either require measured compression ratio and efficiency maps as input values or calculate them “on the fly” throughout specific sub-models integrated in the numerical procedures. Therefore, the ability to correct the measured performance maps taking into account internal heat transfer would allow the implementation of commercial simulation codes used for engine-turbocharger matching calculations.

A multi-objective optimal design of a brushless DC electric motor for a brake system application is presented. Fifteen design variables are considered for the definition of the stator and rotor geometry, pole pieces and permanent magnets included. Target performance indices (peak torque, efficiency, rotor mass and inertia) are defined together with design constraints that refer to components stress levels and temperature thresholds, not to be surpassed after heavy duty cycles. The mathematical models used for optimization refer to electromagnetic field and related currents computation, to thermo-fluid dynamic simulation, to local stress and vibration assessment. An Artificial Neural Network model, trained with an iterative procedure, is employed for global approximation purposes. This allows to reduce the number of simulation runs needed to find the optimal configurations. Some of the Pareto-optimal solutions resulting from the optimal design process are analysed.