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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.

In the face of growing concerns about environmental sustainability and urban congestion, the integration of eco-driving strategies has emerged as a pivotal solution in the field of the urban transportation sector. This study explores the potential benefits of a CAV functioning as a virtual eco-driving controller in an urban traffic scenario with a group of following human-driven vehicles. A computationally inexpensive and realistic powertrain model and energy management system of the Chrysler Pacifica PHEV are developed with the field experiment data and integrated into a forward-looking vehicle simulator to implement and validate an eco-driving speed planning and energy management strategy assuming longitudinal automation. The eco-driving algorithm determines the optimal vehicle speed profile and energy management strategy.

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.

Ammonia is a new type of carbon-free fuel with low cost, clean and safe. The research and application of zero-carbon fuel internal combustion engines has become the mainstream of future development. However, there still exist problems should be solved in the application of ammonia fuel. Due to the lower flame laminar speed and higher ignition temperature, ammonia may have unstable combustion phenomena. In this work, the characteristics of ammonia combustion have been investigated, based on controllable thermal activated atmosphere burner. The ignition delay has been used to analyze the ammonia combustion characteristics. With the increase in co-flow temperature, the ignition delay of ammonia/air has an obvious decline. In order to investigate the emission characteristics of ammonia, CHEMKIN is used to validate the different chemical reaction mechanisms and analyse the ammonia emissions.

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.

Climate change has become a real problem in our world. Society is trying to contain it as much as possible, promoting more sustainable behaviors and limiting pollution. For the automotive industry, this leads to progressive electrification and reduction of tailpipe emissions and fuel consumption for conventional vehicles. In this framework, this paper presents the design of a vehicle to compete in the Urban Concept category of Shell Eco Marathon, a competition among universities that has the goal to release a vehicle with the lowest possible fuel consumption. This work describes the monocoque design phases of the vehicle JUNO. The complete design approach is described, through the analysis of the decisional workflow adopted to integrate every technical solution from the aerodynamic constraints to the structural ones passing from the vehicle dynamic requirements.

The continuous tightening of CO2 emission targets along with the introduction of Real Driving Emissions (RDE) tests make Water Injection (WI) one of the most promising solutions to improve efficiency, enhance performance and reduce emissions of turbocharged high-performance Spark Ignition engines. This technology, by reducing local in-cylinder mixture temperature, enables higher compression ratios, optimal spark timing and stoichiometric combustion over the entire engine operating range. This research activity, therefore, aims to assess the benefits in terms of CO2 emission reduction of a Port Water Injection (PWI) system integrated in a Downsized Turbocharged Direct Injection Spark Ignition (T-DISI) Engine. In this regard, a 1D-CFD model of the engine capable to predict the impact of the water content on both the combustion process and the knock likelihood was firstly developed.

Despite the legislation targets set by several governments of a full electrification of new light-duty vehicle fleets by 2035, the development of innovative, environmental-friendly Internal Combustion Engines (ICEs) is still crucial to be on track toward the complete decarbonization of on road-mobility of the future. In such a framework, the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) project aims at developing a C SUV-class plug-in hybrid (P0/P4) vehicle demonstrator capable to achieve a -10% fuel consumption reduction with respect to current EU6 vehicle while complying with upcoming EU7 pollutant emissions limits. Such ambitious targets will require the optimization of the whole engine system, exploiting the possible synergies among the combustion, the aftertreatment and the exhaust waste heat recovery systems.

The concept of autonomous driving is becoming increasingly familiar in the automotive and “in-door” automation systems fields. Furthermore, the industrial development is focusing its efforts on industry 4.0, whose some main features are data transfer, programming, systems interconnection and automation. The agricultural sector just recently has experienced the first examples of autonomous agricultural vehicles, although agricultural mechanization has reached a good level of automation. Indeed, many examples of automatic machineries are already present in the market such as little robots for the execution of some operations. This work focuses on modelling and simulation of a self-driving orchard tractor. The main goal was to reproduce the behaviour of the specialized vehicle, moving in an orchard or a vineyard and conducting automatic or semi-automatic operations.

Fuel injection systems and performance is fundamental to combustion engine performance in terms of power, noise, efficiency, and exhaust emissions. There is a move toward electric vehicles (EVs) to reduce carbon emissions, but this is unlikely to be a rapid transition, in part due to EV batteries: their size, cost, longevity, and charging capabilities as well as the scarcity of materials to produce them. Until these issues are resolved, refining the spark-ignited engine is necessary to address both sustainability and demand for affordable and reliable mobility. Even under policies oriented to smart sustainable mobility, spark-ignited engines remain strategic, because they can be applied to hybridized EVs or can be fueled with gasoline blended with bioethanol or bio-butanol to drastically reduce particulate matter emissions of direct injection engines in addition to lower CO2 emissions.

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.

In the last years, the design in the automotive sector is mainly led by emission reduction and circular economy. To satisfy the first perspective, composites materials are being increasingly used to produce lightweight structural and semi-structural components. However, the automotive mass production arises the problem of the end-of-life disposal of the vehicle and the reduction of the wastes environmental impact. The circular economy of the composite materials has therefore become a challenge of primary importance for car manufacturers and tier 1 suppliers. It is necessary to pursue a different economic model, combining traditional raw materials with the intensive use of materials from recycling processes. New technologies are being studied and developed concerning the reuse of in-line production scraps with out-of-autoclave process that makes them desirable for high production rate applications.

Fuel cell electrified powertrains are currently a promising technology towards decarbonizing the heavy-duty transportation sector. In this context, extensive research is required to thoroughly assess the hydrogen economy potential of fuel cell heavy-duty electrification. This paper proposes a real-time capable energy management strategy (EMS) that can achieve improved hydrogen economy for a fuel cell electrified heavy-duty truck. The considered heavy-duty truck is modelled first in Simulink® environment. A baseline heuristic map-based controller is then retained that can instantaneously control the electrical power split between fuel cell system and the high-voltage battery pack of the heavy-duty truck. Particle swarm optimization (PSO) is consequently implemented to optimally tune the parameters of the considered EMS.

The use of Ducted Fuel Injection (DFI) for attenuating soot formation throughout mixing-controlled diesel combustion has been demonstrated impressively effective both experimentally and numerically. However, the last research studies have highlighted the need for tailored engine calibration and duct geometry optimization for the full exploitation of the technology potential. Nevertheless, the research gap on the response of DFI combustion to the main engine operating parameters has still to be fully covered. Previous research analysis has been focused on numerical soot-targeted duct geometry optimization in constant-volume vessel conditions. Starting from the optimized duct design, the herein study aims to analyze the influence of several engine operating parameters (i.e. rail pressure, air density, oxygen concentration) on DFI combustion, having free spray results as a reference.

A set of manganese oxide catalysts was synthesized and doped with Cu and/or Fe by means of the citric acid sol-gel preparation method. The samples were studied by means of several characterization techniques: field-emission scanning electron microscopy (FESEM), X-ray powder diffraction (XRD), N2-physisorption at -196 °C, H2 and soot temperature-programmed reduction (H2-TPR, soot-TPR) and X-ray photoelectron spectroscopy (XPS). The catalytic performance of the prepared catalysts was investigated in the oxidation of a probe VOC molecule (propylene) and carbon soot singularly and simultaneously. The catalytic performances were studied as well assuring a content of 5 vol.% of water in the gaseous reactive mix. The investigations evidenced that the best soot catalytic oxidation rates occurred over the Mn2O3 sample, while the copper-doped manganese oxide (i.e. the MnCu15) showed the best performance in the decomposition of propylene.

Nowadays control system development in the automotive industry is evolving rapidly due to several factors. On the one hand legislation tightening is asking for simultaneous emission reduction and efficiency increase, on the other hand the complexity of the powertrain is increasing due to the spreading of electrification. Those factors are pushing for strong design parallelization and frontloading, thus requiring engine calibration to be moved much earlier in the V-Cycle. In this context, this paper shows how, coupling well known physical 1D engine models featuring predictive combustion and emission models with a fully physical aftertreatment system model and longitudinal vehicle model, a powerful virtual test rig can be built. This virtual test rig can be used for powertrain virtual calibration activities with reduced requirement in terms of experimental data.

The detection and evaluation of damage in composite materials components is one of the main concerns for automotive engineers. It is acknowledged that defects appeared in the manufacturing stage or due to the impact and/or fatigue loads can develop along the vehicle riding. To avoid an unexpected failure of structural components, engineers ask for cheap methodologies assessing the health state of composite parts by means of continuous monitoring. Non Destructive Technique (NDT) for the damage assessment of composite structures are nowadays common and accurate, but an on-line monitoring requires properties as low cost, small size and low power that do not belong to common NDT. The presence of a damage in composite materials, either due to fatigue cycling or low-energy impact, leads to progressive degradation of elastic moduli and strengths.

This paper presents a complete overview of the computational design of an advanced suspension control arm constructed of composite material for light weighting purposes. The proposed methodology presented in detail is split into 3 phases. Phase 1 or Vehicle Performance Simulation, in which basic modelling and a sensibility study is performed to better understand the advantages of unsprung mass reduction (compared to sprung mass reduction) with respect to the vehicle’s vertical dynamics. It followed by the development and utilization of a multibody approach to evaluate the full-vehicle response to different dynamic maneuvers, such as harsh road imperfections, sine sweep steering, and double lane change tests. The impact of the improved suspension control arm is highlighted in detail, and the loads to which it is subjected are computed to serve as inputs for the successive phases.

A methodology for an efficient failure prediction of automotive steel wheels during fatigue experimental tests is proposed. The strategy joins the CDTire simulative package effectiveness to a specific wheel finite element model in order to deeply monitor the stress distribution among the component to predict damage. The numerical model acts as a Software-in-the-loop and it is calibrated with experimental data. The developed tool, called VirtualWheel, can be applied for the optimisation of design reducing prototyping and experimental test costs in the development phase. In the first section, the failure criterion is selected. In the second one, the conversion of hardware test-rig into virtual model is described in detail by focusing on critical aspects of finite element modelling. In conclusion, failure prediction is compared with experimental test results.