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Nowadays, green hydrogen can play a crucial role in a successful clean energy transition, thus reaching net zero emissions in the transport sector. Moreover, hydrogen exploitation in internal combustion engines is favoured by its suitable combustion properties and quasi-zero harmful emissions. High flame speeds enable a lean combustion approach, which provides high efficiency and reduces NOx emissions. However, high air flow rates are required to achieve the load levels typical of heavy-duty applications. In this framework, the present study aims to investigate the required boosting system of a 6-cylinder, 13-liter heavy-duty spark ignition engine through 1D numerical simulation. A comparison among various architectures of the turbocharging system and the size of each component is presented, thus highlighting limitations and potentialities of each architecture and providing important insights for the selection of the best turbocharging system.

Traditional CACC systems utilize inter-vehicle wireless communication to maintain minimal yet safe inter-vehicle distances, thereby improving traffic efficiency. However, introducing communication delays generates system uncertainties that jeopardize string stability, a crucial requirement for robust CACC performance. To address these issues, we introduce a decentralized Model Predictive Control (MPC) approach that incorporates Kalman Filters and state predictors to counteract the uncertainties posed by noise and communication delays. We validate our approach through MATLAB Simulink simulations, using stochastic and mathematical models to capture vehicular dynamics, Wi-Fi communication errors, and sensor noises. In addition, we explore the application of a Reinforcement Learning (RL)-based algorithm to compare its merits and limitations against our decentralized MPC controller, considering factors like feasibility and reliability.

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 abatement of carbon dioxide and pollutant emissions on motorbike spark-ignition (SI) engines is a challenging task, considering the small size, the low cost and the high power-to-weight ratio required by the market for such powertrain. In this context, the passive pre-chamber (PPC) technology is an attractive solution. The combustion duration can be reduced by igniting the air-fuel mixture inside a small volume connected to the cylinder, unfolding the way to high engine efficiencies without penalization of the peak performance. Moreover, no injectors are needed inside the PPC, guaranteeing a cheap and fast retrofitting of the existing fleet. In this work, a 3D computational fluid dynamics (CFD) investigation is carried out over an experimental configuration of motorbike SI engine, operated at fixed operating conditions with both traditional and PPC configurations.

This paper presents a numerical methodology to generate lookup tables that provide d- and q-axis stator current references for the control of electric motors. The main novelty with respect to other literature references is the introduction of the iron power losses in the equivalent-circuit electric motor model implemented in the optimization routine. The lookup tables generation algorithm discretizes the motor operating domain and, given proper constraints on maximum stator current and magnetic flux, solves a numerical optimization problem for each possible operating point to determine the combination of d- and q- axis stator currents that minimizes the imposed objective function while generating the desired torque. To demonstrate the versatility of the proposed approach, two different variants of this numerical interpretation of the motor control problem are proposed: Maximum Torque Per Ampere and Minimum Electromagnetic Power Loss.

This paper presents the analysis of an innovative braking system as an alternative and environmentally friendly solution to traditional automotive friction brakes. The idea arose from the need to eliminate emissions from the braking system of an electric vehicle: traditional brakes, in fact, produce dust emissions due to the wear of the pads. The innovative solution, called Zero-Emissions Driving System (ZEDS), is a system composed of an electric motor (in-wheel motor) and an innovative brake. The latter has a geometry such that it houses MagnetoRheological Fluid (MRF) inside it, which can change its viscous properties according to the magnetic field passing through it. It is thus an electro-actuated brake, capable of generating a magnetic field passing through the fluid and developing braking torque. A performance analysis obtained by a simulation model built on Matlab Simulink is proposed.

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.

In the last decades, the locomotion of wheeled and tracked vehicles on soft soils has been widely investigated due to the large interest in planetary, agricultural, and military applications. The development of a tire-soft soil contact model which accurately represents the micro and macro-scale interactions plays a crucial role for the performance assessment in off-road conditions since vehicle traction and handling are strongly influenced by the soil characteristics. In this framework, the analysis of realistic operative conditions turns out to be a challenging research target. In this research work, a semi-empirical model describing the interaction between a tire and homogeneous and fine-grained soils is developed in Matlab/Simulink. The stress distribution and the resulting forces at the contact patch are based on well-known terramechanics theories, such as pressure-sinkage Bekker’s approach and Mohr-Coulomb’s failure criterion.

The design and testing of innovative components and control logics for future vehicular platform represents a challenging task in the automotive field. The use of scale model vehicles constitutes an interesting alternative for testing assessment by decreasing time and cost efforts with a potential benefit in terms of safety. The target of this research work is the development of a customized scale vehicle platform for verifying and validating innovative control strategies in safe conditions and with cost reduction. Consequently, the electrification of a radio-controlled 1:5 scale vehicle is carried out and a customized remote real-time controller is installed onboard. One of the main features of this commercial product is its modular characteristics that allows the modification of some component properties, such as the viscous coefficient of the shock absorbers, the stiffness of the springs and the suspension geometry.

The target of the upcoming automotive emission regulations is to promote a fast transition to near-zero emission vehicles. As such, the range of ambient and operating conditions tested in the homologation cycles is broadening. In this context, the proposed work aims to thoroughly investigate the potential of post-oxidation phenomena in reducing the light-off time of a conventional three-way catalyst. The study is carried out on a turbocharged four-cylinder gasoline engine by means of experimental and numerical activities. Post oxidation is achieved through the oxidation of unburned fuel in the exhaust line, exploiting a rich combustion and a secondary air injection dedicated strategy. The CFD methodology consists of two different approaches: the former relies on a full-engine mesh, the latter on a detailed analysis of the chemical reactions occurring in the exhaust line.

Nowadays numerical simulations play a major role in the development of future sustainable powertrain thanks to their capability of investigating a wide spectrum of innovative technologies with times and costs significantly lower than a campaign of experimental tests. In such a framework, this paper aims to assess the predictive capabilities of an 1D-CFD engine model developed to support the design and the calibration of the innovative highly efficient spark ignition engine of the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) EU H2020 project. As a matter of fact, the availability of a reliable simulation platform is crucial to achieve the project target of 47% peak indicating efficiency, by synergistically exploiting the combination of innovative in-cylinder charge motion, Miller cycle with high compression ratio, lean mixture with cooled Exhaust Gas Recirculation (EGR) and electrified turbocharger.

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.

In the rapidly changing scenario of the energy transition, data-driven tools for kinetic mechanism development and testing can greatly support the evaluation of the combustion properties of new potential e-fuels. Despite the effectiveness of kinetic mechanism generation and optimization procedures and the increased availability of experimental data, integrated methodologies combining data analysis, kinetic simulations, chemical lumping, and kinetic mechanism optimization are still lacking. This paper presents an integrated workflow that combines recently developed automated tools for kinetic mechanism development and testing, from data collection to kinetic model reduction and optimization. The proposed methodology is applied to build a consistent, efficient, and well-performing kinetic mechanism for the combustion of oxymethylene ethers (OMEs), which are promising synthetic e-fuels for transportation.

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.

The current electrification trend involving hybrid and electric vehicles requires accurate tools to evaluate performance and reliability of electric powertrains’ control systems. Thanks to Hardware in the Loop (HiL) technique, verification, validation and virtual calibration of Electronic Control Systems can be performed without physical plants, addressing the need of frontloading, cost and time reduction of new vehicles control systems development. However, HiL applications with power electronics controllers brings several concerns due to the extremely low timestep needed for accurate simulation of electromagnetic phenomena, making FPGA-based simulation the only option. Moreover, thermal aspects of electric motors are very important from the control perspective as complex thermal management control strategies are implemented to improve the efficiency and to prevent overheating that can cause permanent damage to the electrical machine.

In future decarbonized scenarios, hydrogen is widely considered as one of the best alternative fuels for internal combustion engines, allowing to achieve zero CO2 emissions at the tailpipe. However, NOx emissions represent the predominant pollutants and their production has to be controlled. In this work different strategies for the control and abatement of pollutant emissions on a H2-fueled high-performance V8 twin turbo 3.9L IC engine are tested. The characterization of pollutant production on a single-cylinder configuration is carried out by means of the 1D code Gasdyn, considering lean and homogeneous conditions. The NOx are extremely low in lean conditions with respect to the emissions legislation limits, while the maximum mass flow rate remains below the turbocharger technical constraint limit at λ=1 only.