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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.

The issue of greenhouse gas (GHG) emissions from the transportation sector is widely acknowledged. Recent years have witnessed a push towards the electrification of cars, with many considering it the optimal solution to address this problem. However, the substantial battery packs utilized in electric vehicles contribute to a considerable embedded ecological footprint. Research has highlighted that, depending on the vehicle's size, tens or even hundreds of thousands of kilometers are required to offset this environmental burden. Human-powered vehicles (HPVs), thanks to their smaller size, are inherently much cleaner means of transportation, yet their limited speed impedes widespread adoption for mid-range and long-range trips, favoring cars, especially in rural areas. This paper addresses the challenge of HPV speed, limited by their low input power and non-optimal distribution of the resistive forces.

Range anxiety in current battery electric vehicles is a challenging problem, especially for commercial vehicles with heavy payloads. Therefore, the development of electrified propulsion systems with multiple power sources, such as fuel cells, is an active area of research. Optimal speed planning and energy management, referred to as eco-driving, can substantially reduce the energy consumption of commercial vehicles, regardless of the powertrain architecture. Eco-driving controllers can leverage look-ahead route information such as road grade, speed limits, and signalized intersections to perform velocity profile smoothing, resulting in reduced energy consumption. This study presents a comprehensive analysis of the performance of an eco-driving controller for fuel cell electric trucks in a real-world scenario, considering a route from a distribution center to the associated supermarket.

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 role of numerical simulations in the development of innovative and sustainable powertrains is constantly growing thanks to their capabilities to significantly reduce the calibration efforts and to point out potential synergies among different technologies. In such a framework, this paper describes the development of a fully physical 1D-CFD engine model to support the calibration of the highly efficient spark ignition engine of the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) EU H2020 project. The availability of a reliable simulation platform is essential to effectively exploit the combination of the several features introduced to achieve the project target of 47% peak gross indicated efficiency, such as SwumbleTM in-cylinder charge motion, Miller cycle combined with high Compression Ratio (CR), lean mixture exploiting cooled low pressure Exhaust Gas Recirculation (EGR) and electrified turbocharging.

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.

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.

In the framework of an increasing demand for a more sustainable mobility, where the fuel consumption reduction is a key driver for the development of innovative internal combustion engines, Turbulent Jet Ignition (TJI) represents one of the most promising solutions to improve the thermal efficiency. However, details concerning turbulent jet assisted combustion are still to be fully captured, and therefore the design and the calibration of efficient TJI systems require the support of reliable simulation tools that can provide additional information not accessible through experiments. To this aim, an experimental investigation combined with a 3D-CFD study was performed to analyze the TJI combustion characteristics in a single-cylinder spark-ignition (SI) engine. Firstly, the model was validated against experiments considering stoichiometric mixture at 3000 rpm, wide open throttle operating conditions.

Diesel engines with their embedded control systems are becoming increasingly complex as the emission regulations tighten, especially concerning NOx pollutants. The combustion and emission formation processes are closely correlated to the intake manifold O2 concentration. Consequently, the performance of the engine controllers can be improved if a model-based or sensor-based estimation of the O2 concentration is available. The paper addresses the modeling of the O2 concentration in a turbocharged diesel engine. Dynamic models, compared to generally employed steady state maps, capture the dynamic effects occurring over transients, when the major deviations from the stationary maps are found. Dynamic models positively affect the control system making it more effective and, exploiting information coming from sensors, they provide a more robust prediction performance. Firstly, a Nonlinear Output Error model (NOE), with simulation focus, fed with four inputs is presented.

As an era of autonomous driving approaches, it is necessary to translate handling comfort - currently a responsibility of human drivers - to a vehicle imbedded algorithm. Therefore, it is imperative to understand the relationship between perceived driving comfort and human driving behaviour. This paper develops a methodology able to generate the information necessary to study how this relationship is expressed in highway overtakes. To achieve this goal, the approach revolved around the implementation of sensor Data Fusion, by processing data from CAN, camera and LIDAR from experimental tests. A myriad of variables was available, requiring individuating the key-information and parameters for recognition, classification and understanding of the manoeuvres. The paper presents the methodology and the role each sensor plays, by expanding on three main steps: Data segregation and parameter selection; Manoeuvre detection and processing; Manoeuvre classification and database generation.

During some critical maneuvers, transmission systems using Dual Mass Flywheel (DMF) may experience overtorques, which could lead to structural damages of the transmission components. In a dual mass flywheel, total inertia is divided into two parts: a primary mass connected to the engine and a secondary mass to the transmission. The torque delivered by the engine is transferred from one mass to the other through a drive plate and a set of arc springs, the latter absorbing the torsional oscillations coming from internal combustion engine and the shocks caused by fast clutch engagements. This paper investigates overtorque issues and proposes a solution based on a torque limiter, consisting of a friction clutch inserted between the two masses, that limits the maximum torque transmitted through it. The basic idea is to replace the classic flat drive plate with a tapered drive plate that functions as a Belleville spring.

Developing of innovative technologies and materials to meet the requirements of environmental legislation on vehicle emissions has paramount importance for researchers and industries. Therefore, improvement of engine efficiency and fuel saving of modern internal combustion engines (ICEs) is one of the key factors, together with the weight reduction. Thermoplastic composite materials might be one of the alternative materials to be employed to produce engine components to achieve these goals as their properties can be engineered to meet application requirements. Unidirectional carbon fiber reinforced PolyEtherImide (CF/PEI) thermoplastic composite is used to design engine connecting rod and wrist pin, applying commercial engine data and geometries. The current study is focused on some elements of the crank mechanism as the weight reduction of these elements affects not only the curb weight of the engine but the overall structure.

In automotive market, today more than in the past, it is very important to reduce time to market and, mostly, developing costs before the final production start. Ideally, bench and on-road tests can be replaced by multi-body studies because virtual approach guarantees test conditions very close to reality and it is able to exactly replicate the standard procedures. Therefore, today, it is essential to create very reliable models, able to forecast the vehicle behavior on every road condition (including uneven surfaces). The aim of this study is to build an accurate multi-body model of a heavy-duty truck, check its handling performance, and correlate experimental and numerical data related to comfort tests for model tuning and validation purposes. Experimental results are recorded during tests carried out at different speeds and loading conditions on a Belgian blocks track. Simulation data are obtained reproducing the on-road test conditions in multi-body environment.

The aim of this paper is to study in deep the peculiar test-rigs and experimental procedures adopted to the fulfilment of the principal requirements of automotive steel wheels, in particular regarding fatigue damaging. In the discussion, the standard requirements, the OEM specifications and the dimensional and geometric tolerances are approached. As result of an increasingly necessity to improve the performance of the components, innovative virtual test benches are presented. Differently from their traditional precursors, virtual test-rigs give an extended view of the physical behaviour of the component as the possibility to monitor stress-strain distribution in deep. In the first section, the state of the art and the specifications are listed. Secondly, the adopted hardware test-rigs as the experimental tests are described in detail. In the third one, proposed virtual test-rig is discussed.

Hybrid electric vehicles (HEVs) represent a fundamental step in the global evolution towards transportation electrification. Nevertheless, they exhibit a remarkably complex design environment with respect to both traditional internal combustion engine vehicles and battery electric vehicles. Innovative and advanced design tools are therefore crucially required to effectively handle the increased complexity of HEV development processes. This paper aims at providing a comprehensive overview of past and current advancements in HEV powertrain design methodologies. Subsequently, major simplifications and limits of current HEV design methodologies are detailed. The final part of this paper defines research challenges that need accomplishment to develop the next generation HEV architecture design tools.

Until 2017 in Europe the Type Approval (TA) procedure for light duty vehicles for the determination of pollutant emissions and fuel consumption was based on the New European Driving Cycle (NEDC), a test cycle performed on a chassis dynamometer. However several studies highlighted significant discrepancies in terms of CO2 emissions between the TA test and the real world, due to the limited representativeness of the test procedure. Therefore, the European authorities decided to introduce a new, up-to date, test procedure capable to closer represent real world driving conditions, called Worldwide Harmonized Light Vehicles Test Procedure (WLTP). This work aims to analyze the effects of the new WLTP on vehicle CO2 emissions through both experimental and simulation investigations on two different Euro 5 vehicles, a petrol and a diesel car, representatives of average European passenger cars.

In this paper, a numerical and experimental assessment of post injection potential for soot emissions mitigation in an off-road diesel engine is presented, with the aim of supporting hardware selection and engine calibration processes. As a case study, a prototype off-road 3.4 liters 4-cylinder diesel engine developed by Kohler Engines was selected. In order to explore the possibility to comply with Stage V emission standards without a dedicated aftertreatment for NOx, the engine was equipped with a low pressure cooled Exhaust Gas Recirculation (EGR), allowing high EGR rates (above 30%) even at high load. To enable the exploitation of such high EGR rates with acceptable soot penalties, a two-stage turbocharger and an extremely high-pressure fuel injection system (up to 3000 bar) were adopted. Moreover, post injections events were also exploited to further mitigate soot emissions with acceptable Brake Specific Fuel Consumption (BSFC) penalties.

In order to meet the CO2 emission reduction targets, downsizing coupled with turbocharging has been proven as an effective way in reducing CO2 emissions while maintaining and improving vehicle driveability. As the downsizing becomes widely exploited, the increased boost levels entail the exploration of dual stage boosting systems. In a context of increasing electrification, the usage of electrified boosting systems can be effective in the improvement of vehicle performances. The aim of this work is therefore to evaluate, through numerical simulation, the impact of different voltage (12 V or 48 V) electric superchargers (eSC) on an extremely downsized 1.0L engine on vehicle performance and fuel consumption over different transient manoeuvres.

A comprehensive experimental and numerical analysis of two state-of-the-art diesel AfterTreatment Systems (ATS) for automotive applications is presented in this work. Both systems, designed to fulfill Euro 6 emissions regulations standards, consist of a closed-coupled Diesel Oxidation Catalyst (DOC) followed by a Selective Catalytic Reduction (SCR) catalyst coated on a Diesel Particulate Filter (DPF), also known as SCR on Filter (SCRoF or SCRF). While the two systems feature the same Urea Water Solution (UWS) injector, major differences could be observed in the UWS mixing device, which is placed upstream of the SCRoF, whose design represents a crucial challenge due to the severe flow uniformity and compact packaging requirements.

The demanding CO2 emission targets are fostering the development of downsized, turbocharged and electrified engines. In this context, the need for high boost level at low engine speed requires the exploration of dual stage boosting systems. At the same time, the increased electrification level of the vehicles enables the usage of electrified boosting systems aiming to exploit the opportunities of high levels of electric power and energy available on-board. The aim of this work is therefore to evaluate, through numerical simulation, the impact of a 48 V electric supercharger (eSC) on vehicle performance and fuel consumption over different transients. The virtual test rig employed for the analysis integrates a 1D CFD fast running engine model representative of a 1.5 L state-of-the-art gasoline engine featuring an eSC in series with the main turbocharger, a dual voltage electric network (12 V + 48 V), a six-speed manual transmission and a vehicle representative of a B-SUV segment car.