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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.

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.

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.

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.

Natural gas is a promising alternative fuel for internal combustion engine application due to its low carbon content and high knock resistance. Performance of natural gas engines is further improved if direct injection, high turbocharger boost level, and variable valve actuation (VVA) are adopted. Also, relevant efficiency benefits can be obtained through downsizing. However, mixture quality resulting from direct gas injection has proven to be problematic. This work aims at developing a mono-fuel small-displacement turbocharged compressed natural gas engine with side-mounted direct injector and advanced VVA system. An injector configuration was designed in order to enhance the overall engine tumble and thus overcome low penetration.

Flow control over aerodynamic shapes in order to achieve performance enhancements has been a lively research area for last two decades. Synthetic Jet Actuators (SJAs) are devices able to interact actively with the flow around their hosting structure by providing ejection and suction of fluid from the enclosed cavity containing a piezo-electric oscillating membrane through dedicated orifices. The research presented in this paper concerns the implementation of zero-net-mass-flux SJAs airflow control system on a NACA0015, low aspect ratio wing section prototype. Two arrays with each 10 custom-made SJAs, installed at 10% and 65% of the chord length, make up the actuation system. The sensing system consists of eleven acoustic pressure transducers distributed in the wing upper surface and on the flap, an accelerometer placed in proximity of the wing c.g. and a six-axis force balance for integral load measurement.

The concept of Partially Premixed Combustion is known for reduced hazardous emissions and improved efficiency. Since a low-reactive fuel is required to extend the ignition delay at elevated loads, controllability and stability issues occur at the low-load end. In this investigation seven fuel blends are used, all having a Research Octane Number of around 70 and a distinct composition or boiling range. Four of them could be regarded as ‘viable refinery fuels’ since they are based on current refinery feedstocks. The latter three are based on primary reference fuels, being PRF70 and blends with ethanol and toluene respectively. Previous experiments revealed significant ignition differences, which asked for further understanding with an extended set of measurements. Experiments are conducted on a heavy duty diesel engine modified for single cylinder operation. In this investigation, emphasis is put on idling (600 rpm) and low load conditions.

Sustainable mobility has become a major issue for internal combustion engines and has led to increasing research efforts in the field of alternative fuels, such as bio-fuel, CNG and hydrogen addition, as well as into engine design and control optimization. To that end, a thorough control of the air-to-fuel ratio appears to be mandatory in SI engine in order to meet the even more stringent thresholds set by the current regulations. The accuracy of the air/fuel mixture highly depends on the injection system dynamic behavior and to its coupling to the engine fluid-dynamic. Thus, a sound investigation into the mixing process can only be achieved provided that a proper analysis of the injection rail and of the injectors is carried out. The present paper carries out a numerical investigation into the fluid dynamic behavior of a commercial CNG injection system by means of a 0D-1D code.

The effects of using blended renewable diesel fuel (30% vol.), obtained from Rapeseed Methyl Ester (RME) and Hydrotreated Vegetable Oil (HVO), in a Euro 5 small displacement passenger car diesel engine have been evaluated in this paper. The hydraulic behavior of the common rail injection system was verified in terms of injected volume and injection rate with both RME and HVO blends fuelling in comparison with commercial diesel. Further, the spray obtained with RME B30 was analyzed and compared with diesel in terms of global shape and penetration, to investigate the potential differences in the air-fuel mixing process. Then, the impact of a biofuel blend usage on engine performance at full load was first analyzed, adopting the same reference calibration for all the tested fuels.

An experimental investigation was performed on a turbocharged spark-ignition 4-cylinder production engine fuelled with natural gas and with two blends of natural gas and hydrogen (15% and 25% in volume of H₂). The engine was purposely designed to give optimal performance when running on CNG. The first part of the experimental campaign was carried out at MBT timing under stoichiometric conditions: load sweeps at constant engine speed and speed sweeps at constant load were performed. Afterwards, spark advance sweeps and relative air/fuel ratio sweeps were acquired at constant engine speed and load. The three fuels were compared in terms of performance (fuel conversion efficiency, brake specific fuel consumption, brake specific energy consumption and indicated mean effective pressure) and brake specific emissions (THC, NOx, CO).

This paper presents the results of part of the research activity carried out by the Politecnico di Torino and AVL List GmbH as part of the European Community InGAS Collaborative Project. The work was aimed at developing a combustion system for a mono-fuel turbocharged CNG engine, with specific focus on performance, fuel economy and emissions. A numerical and experimental analysis of the jet development and mixture formation in an optically accessible, single cylinder engine is presented in the paper. The experimental investigations were performed at the AVL laboratories by means of the planar laser-induced fluorescence technique, and revealed a cycle-to-cycle jet shape variability that depended, amongst others, on the injector characteristics and in-cylinder backpressure. Moreover, the mixing mechanism had to be optimized over a wide range of operating conditions, under both stratified lean and homogeneous stoichiometric modes.

Future exploration missions, including human missions to the Moon and Mars, are expected to have increasingly demanding operational requirements. Generating electrical power, and also maintaining a specific thermal environment, are both critical capabilities for any mission. In the case of exploration, both a wide range of mission types (robotic, human, ISRU etc.) and a variety of environments exist: from interplanetary space, to the shadow of a lunar crater, to the attenuated and red-shifted lighting on the Martian surface, power requirements must be met. This objective could be met with different technologies. The choice is dictated by the operating conditions and the different types of mission. TAS-I is historically mainly involved in missions related to the space exploration with the presence of astronauts. A typical example is the exploration of the Moon with the installation on the Moon surface of a base inclusive of pressurized habitats and rovers.

The effects of using neat and blended (30% vol.) biodiesel, obtained from Rapeseed Methyl Ester (RME) and Jatropha Methyl Ester (JME), in a Euro 5 small displacement passenger car diesel engine have been evaluated in this paper. The impact of biodiesel usage on engine performance at full load was analyzed for a specifically adjusted ECU calibration: the same torque levels measured under diesel operation could be obtained, with lower smoke levels, thus highlighting the potential for maintaining the same level of performance while achieving substantial emissions benefits. In addition, the effects of biodiesel blends on brake-specific fuel consumption and on engine-out exhaust emissions (CO₂, CO, HC, NOx and smoke) were also evaluated at 6 different part load operating conditions, representative of the New European Driving Cycle. Emissions were also measured at the DPF outlet, thus providing information about after-treatment devices efficiencies with biodiesel.

In Motorsports the understanding of the real engine performance within a complete circuit lap is a crucial topic. On the basis of the telemetry data the engineers are able to monitor this performance and try to adapt the engine to the vehicle's and race track's characteristics and driver's needs. However, quite often the telemetry is the sole analysis instrument for the Engine-Vehicle-Driver (EVD) system and it has no prediction capability. The engine optimization for best lap-time or best fuel economy is therefore a topic which is not trivial to solve, without the aid of suitable, reliable and predictive engineering tools. A complete EVD model was therefore built in a GT-SUITE™ environment for a Motorsport racing car (STCC-VW-Scirocco) equipped with a Compressed Natural Gas (CNG) turbocharged S.I. engine and calibrated on the basis of telemetry and test bench data.

Experimental work was carried out on a small displacement Euro 5 automotive diesel engine alternatively fuelled with ultra low sulphur diesel (ULSD) and with two blends (30% vol.) of ULSD and of two different fatty acid methyl esters (FAME) obtained from both rapeseed methyl ester (RME) and jatropha methyl ester (JME) in order to evaluate the effects of different fuel compositions on particle number (PN) emissions. Particulate matter (PM) emissions for each fuel were characterized in terms of number and mass size distributions by means of two stage dilutions system coupled with a scanning mobility particle sizer (SMPS). Measurements were performed at three different sampling points along the exhaust system: at engine-out, downstream of the diesel oxidation catalyst (DOC) and downstream of the diesel particulate filter (DPF). Thus, it was possible to evaluate both the effects of combustion and after-treatment efficiencies on each of the tested fuels.