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In pursuing sustainable automotive technologies, exploring alternative fuels for hybrid vehicles is crucial in reducing environmental impact and aligning with global carbon emission reduction goals. This work compares methanol and naphtha as potential suitable alternative fuels for running in a battery-driven light-duty hybrid vehicle by comparing their performance with the diesel baseline engine. This work employs a 0-D vehicle simulation model within the GT-Power suite to replicate vehicle dynamics under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC). The vehicle choice enables the assessment of a delivery application scenario using distinct payload capacities: 0%, 25%, 50%, and 100%. The model is fed with engine maps derived from previous experimental work conducted in the same engine, in which a full calibration was obtained that ensures the engine's operability in a wide region of rotational speed and loads.

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.

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.

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 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.

Accelerating rate calorimetry (ARC) has emerged as a powerful tool for evaluating the thermal behavior of Li-ion cells and identifying potential safety hazards. In this work, a new physical thermal model has been developed based on the first law of thermodynamics for analyzing heat and mass generated by Lithium-ion battery cells under thermal abuse conditions during EV-ARC tests. The analysis is based on the experimental data gathered from an ARC, including different temperatures and pressure inside a gas-tight canister located in the calorimeter chamber, as well as the gas composition at the end of the test. The energy balance of the battery cell includes: the energy released by the cell, the internal energy of the elements inside the canister, heat transfer between elements inside the canister, as well as the mass transfer between the cell and the gases inside the canister.

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.

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.

Focusing on the dual-mode dual-fuel (DMDF) combustion concept, a combined optimization of the piston bowl geometry with the fuel injection strategy was conducted at low, mid, and high loads. By coupling the KIVA-3V code with the enhanced genetic algorithm (GA), a total of 14 parameters including the piston bowl geometric parameters and the injection parameters were optimized with the objective of meeting Euro VI regulations while improving the fuel efficiency. The optimal piston bowl shape coupled with the corresponding injection strategy was summarized and integrated at various loads. Furthermore, the effects of the key geometric parameters were investigated in terms of organizing the in-cylinder flow, influencing the energy distribution, and affecting the emissions. The results indicate that the behavior of the DMDF combustion mode is further enhanced in the aspects of improving the fuel economy and controlling the emissions after the bowl geometry optimization.

The paper illustrates and validates a novel predictive combustion model for the estimation of performances and pollutant production in CI engines. The numerical methodology was developed by the authors for near real-time applications, while aiming at an accurate description of the air mixing process by means of a multi-zone approach of the air-fuel mass. Charge stratification is estimated via a 2D representation of the fuel spray distribution that is numerically derived by an axial one-dimensional control-volume description of the direct injection. The radial coordinate of each control volume is reconstructed a posteriori by means of a local distribution function. Fuel mass clustered in each zone is further split in ‘liquid’, ‘unburnt’ and ‘burnt’ sub-zones, given the local properties of the fuel spray control volumes with respect to space-time location of modelled ignition delay, liquid length, and flame lift-off.

The temperature of fuel injectors can affect the flow inside nozzles and the subsequent spray and liquid films on the injector tips. These processes are known to impact fuel mixing, combustion and the formation of deposits that can cause engines to go off calibration. However, there is a lack of experimental data for the transient evolution of nozzle temperature throughout engine cycles and the effect of operating conditions on injector tip temperature. Although some measurements of engine surface temperature exist, they have relatively low temporal resolutions and cannot be applied to production injectors due to the requirement for a specialist coating which can interfere with the orifice geometry. To address this knowledge gap, we have developed a high-speed infrared imaging approach to measure the temperature of the nozzle surface inside an optical diesel engine.

The continuous improvement of internal combustion engines (ICEs) with strategies that can be applied to existing vehicle platforms, either directly or with minor modifications, can improve efficiency and reduce GHG emissions to help achieve Paris climate targets. Low carbon fuels (LCF) as diesel substitutes for light and heavy-duty vehicles are currently being considered as a promising alternative to reduce well-to-wheel (WTW) CO2 emissions by taking advantage of the carbon offset their synthesis pathway can promote, which could capture more CO2 than it releases into the atmosphere. Additionally, some low carbon fuels, like OMEx blends, have non-sooting properties that can significantly improve the NOx-soot tradeoff. The current work studies the calibration optimization of a EU6D-TEMP light-duty engine using various LCFs with different renewable contents with the goal of reduced NOx emissions.

In the next years, the upcoming emission legislations are expected to introduce further restrictions on the admittable level of pollutants from vehicles measured on homologation cycles and real drive tests. In this context, the strict control of pollutant emissions at the cold start will become a crucial point to comply with the new regulation standards. This will necessarily require the implementation of novel strategies to speed-up the light-off of the reactions occurring in the after-treatment system, since the cold start conditions are the most critical one for cumulative emissions. Among the different possible technological solutions, this paper focuses on the evaluation of the potential of a burner system, which is activated before the engine start. The hypothetical burner exploits the lean combustion of an air-gasoline mixture to generate a high temperature gas stream which is directed to the catalyst section promoting a fast heating of the substrate.

Low pressure exhaust gases recirculation (LP-EGR) is becoming a state-of-the-art technique for Nitrogen oxides (NOx) reduction in compression ignited (CI) engines. However, despite the pollutant reduction benefits, LP-EGR suffers from strong non-linearities and delays which are difficult to handle, resulting in reduced engine performance under certain conditions. Measurement and observation of oxygen concentration at the intake have been a research topic over the past few years, and it may be critical for transition phases (from low pressure to high pressure EGR). Here, an adequate selection of models and sensors is essential to obtain a precise and fast measurement for control purposes. The present paper analyses different sensor configurations, with oxygen concentration measurements at the intake and exhaust manifold and combines observation techniques with sensor models to determine the potential of each configuration.

The paper investigates the dynamics of the tire and brake during hard braking or wheel locking, from the view point of a brake manufacturer. A new test rig, named BRAD (BRembo Automotive Dynamometer) is presented which measures the forces acting both at the brake and at the tire-ground interface. Lateral forces are not measured. In the test rig, the ground is represented by a drum. The features of the test rig are presented. The measurement accuracy is declared. The first result is that, near wheel locking, a substantial part of the braking power is generated by the tire and not by the brake. The test rig quantifies such a partitioning of brake power, which is important for current and future electric motorsport activities. Some 30% of the braking power is due to tire during hard braking. The second result is that, due to such important braking power at the tire, the tire is heated up, which increases considerably the maximum friction.

In recent years, the increase of gasoline fuel injection pressure is a way to improve thermal efficiency and lower engine-out emissions in GDI homogenous combustion concept. The challenge of controlling particulate formation as well in mass and number concentrations imposed by emissions regulations can be pursued improving the mixture preparation process and avoiding mixture inhomogeneity with ultra-high injection pressure values up to 100 MPa. The increase of the fuel injection pressure in GDI homogeneous systems meets the demand for increased injector static flow, while simultaneously improves the spray atomization and mixing characteristics with consequent better combustion performance. Few studies quantify the effects of high injection pressure on transient gasoline spray evolution. The aim of this work was to simulate with OpenFOAM the spray morphology of a commercial gasoline injected in a constant volume vessel by a prototypal GDI injector.

A comparison of the flame structure for two different fuels, dodecane and oxymethylene dimethyl ether (OMEX), has been performed under condition of Spray A of the Engine Combustion Network (ECN). The experiments were carried out in a constant pressure vessel with wide optical access, at high pressure and temperature and controlled oxygen concentration. The flame structure analysis has been performed by measuring the formaldehyde and OH radical distributions using planar Laser-Induced Fluorescence (PLIF) techniques. To complement the analysis, this information was combined with that obtained with high-speed imaging of OH* chemiluminescence radiation in the UV. Formaldehyde molecules are excited with the 355-nm radiation from the third harmonic of a Nd:YAG laser, whilst OH is excited with a wavelength of 281.00-nm from a dye laser.

The reliable prediction of pollutant emissions generated by IC engine powertrains during the WLTP driving cycle is a key aspect to test and optimize different configurations, in order to respect the stringent emission limits. This work describes the application of an integrated modeling tool in a co-simulation environment, coupling a 1D fluid dynamic code for engine simulation with a specific numerical code for aftertreatment modelling by means of a robust numerical approach, to achieve a complete methodology for detailed simulations of driving cycles. The main goal is to allow an accurate 1D simulation of the unsteady flows along the intake and exhaust systems and to apply advanced thermodynamic combustion models for the calculation of cylinder-out emissions.

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.

Aqueous Urea is a non-toxic and stable ammonia carrier and its injection and mixing represent the basis for the most common de-NOx technology for mobile applications. The reactant feed preparation process is defined by evaporation, thermolysis and hydrolysis of the liquid mixture upstream the Selective Catalytic Reduction reactor, and it is strongly dependent on the interaction between spray and gaseous flow. Low-pressure driven injectors are the common industrial standard for these applications, and their behavior in almost-ambient pressure cross flows is significantly different from any in-cylinder application. For this reason, two substantially different injectors in terms of geometry and design are experimentally studied, characterizing drop sizes and velocities through Phase Doppler Anemometry (PDA) and liquid mass spatial distribution through Shadow Imaging (SI).