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Plug-in Hybrid Electric Vehicles (PHEVs) are one of the main technology options for reducing vehicle CO2 emissions and helping vehicle manufacturers (OEMs) to meet the CO2 targets set by different Governments from all around the world. In Europe OEMs have introduced a number of PHEV models to meet their CO2 target of 95 g/km for passenger cars set for the year 2021. Fuel consumption (FC) and CO2 emissions from PHEVs, however, strongly depend on the way they are used and on the frequency with which their battery is charged by the user. Studies have indeed revealed that in real life, with poor charging behavior from users, PHEV FC is equivalent to that of conventional vehicles, and in some cases higher, due to the increased mass and the need to keep the battery at a certain charging level.

In this paper a test bench for measuring the Static Transmission Error of two mating gears is presented and a comparison with the results obtained with the commercial software GeDy TrAss is shown. Static Transmission Error is considered as the main source of overloads and Noise, Vibration and Harshness issues in mechanical transmissions. It is defined as the difference between the theoretical angular position of two gears under load in quasi-static conditions and the real one. This parameter strictly depends on the applied torque and the tooth macro and micro-geometry. The test bench illustrated in this work is designed to evaluate the actual Static Transmission Error of two gears under load in quasi-static conditions. In particular, this testbed can be divided in two macro elements: the first one is the mechanism composed by weights and pulleys that generates a driving and a braking torque up to 500 Nm.

A fuel-cell-based system's performance is mainly identified in the overall efficiency, strongly depending on the amount of power losses due to auxiliary devices to supply. In such a situation, everything that causes either a decrease of the available power output or an increment of auxiliary losses would determine a sensible overall efficiency reduction.

This paper describes the optimization of the layout and of the control strategy of through-the-road (TTR) parallel hybrid electric vehicles equipped with two compression-ignition engines that feature different values of maximum output power. First, a tool has been developed to define the optimal layout of each TTR vehicle. This is based on the minimization of the powertrain and fuel cost over a 10-year time span, taking into account the fuel consumption. Several performance requirements are guaranteed during the optimization, namely maximum vehicle velocity, 0-100 km/h acceleration time, gradeability and the all-electric range. A benchmark optimizer that is based on the dynamic programming theory has been developed to identify the optimal working mode and the gear number, which are the control variables of the problem. A mathematical technique, based on the pre-processing of a configuration matrix, has been developed in order to speed up the calculation time.

An experimental investigation on a group of unleaded gasolines of different chemical composition has been carried out, in order to analyze their knock behaviour in a mass-produced engine at high revolution speed, to highlight possible inconsistencies with their standard Research and Motor octane numbers and to try to discover explanations for the abovementioned inconsistencies. The investigation has been focused on fuels containing oxygenated compounds, such as alcohols (methanol and ethanol) and ethers (MTBE), with the aim of pointing out the influence of the fuel composition on the octane rating, especially as far as the variation in the stoichiometric air/fuel ratio (due to oxygenated compounds blending) is concerned. In particular, the rating of all the fuels under the same relative air/fuel ratio has shown to be a mandatory condition in order to obtain a proper estimate of antiknock performances. The evaluations obtained are consistent with the standard Motor octane numbers.

Development trends in modern common rail fuel injection systems (FIS) show dramatically increasing capabilities in terms of optimization of the fuel injection strategy through a constantly increasing number of injection events per engine cycle as well as through the modulation and shaping of the injection rate. In order to fully exploit the potential of the abovementioned fuel injection strategy optimization, numerical simulation can play a fundamental role by allowing the creation of a kind of a virtual test rig, where the input is the fuel injection rate and the optimization targets are the combustion outputs, such as the burn rate, the pollutant emissions, and the combustion noise (CN).

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.

During the past few years substantial advances have been made in reducing the drag of automobiles. Future improvements are becoming increasingly difficult to achieve; for this reason more-advanced flow investigation methods are required. This paper shows some results of flow analysis performed using two methods. The first is experimental and is based on car-wake flow surveying; the second is computational and is based on inviscid flow calculations simply corrected for viscous effects. The two methods may be usefully combined.

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.

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.

XAM is a two-seat city vehicle prototype developed at the Politecnico di Torino, equipped with a hybrid propulsion system to obtain low consumptions and reduced environmental impact. The design of this vehicle was guided by the requirements of weight reduction and aerodynamic optimization of the body, aimed at obtaining a reduction of resistance while guarantying roominess. The basic shape of the vehicle corresponding to the requirements of style, ergonomics and structure were deeply studied through CFD simulation in order to assess its aerodynamic performance (considering the vehicle as a whole or the influence of the various details and of their changes separately). The most critical areas of the body (underfloor, tail, spoiler, mirrors, A-pillar) were analyzed creating dedicated refinement volumes.

The Vehicle Energy Consumption calculation Tool (VECTO) is used in Europe for calculating standardised energy consumption and CO2 emissions from Heavy-Duty Trucks (HDTs) for certification purposes. The tool requires detailed vehicle technical specifications and a series of component efficiency maps, which are difficult to retrieve for those that are outside of the manufacturing industry. In the context of quantifying HDT CO2 emissions, the Joint Research Centre (JRC) of the European Commission received VECTO simulation data of the 2016 vehicle fleet from the vehicle manufacturers. In previous work, this simulation data has been normalised to compensate for differences and issues in the quality of the input data used to run the simulations. This work, which is a continuation of the previous exercise, focuses on the deeper meaning of the data received to understand the factors contributing to energy and fuel consumption.

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.

Automotive manufacturers are facing stronger and stronger pressure to optimize all aspects related to fuel consumption of cars, and aerodynamic drag makes no exception, due to increasing government enforcing rules for the reduction of the emissions and the increasing influence of aerodynamic performance on fuel consumption with WLTC and RDE driving cycles. Nowadays, CFD simulation is a common tool across automotive industries for the assessment and the optimization of vehicle resistance in the design phase. The full power of these numerical methods of studying many design variants in advance of experimental testing, however, can be fully exploited when coupled with optimization techniques, always keeping into account constraints and aesthetical demands. On the other hand, a massive use of CFD optimization can lead to unaffordable computational efforts or a limitation of the design exploration space.

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.

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.

A prototype vehicle (PV) is equipped to test powertrain and active chassis systems with innovative control strategies for safety and energy saving. Additional sensors installed on-board allow the measurement and estimation of new information useful to the vehicle dynamic control. The PV was based on a serial production passenger car with Electronic Stability Control (ESC). Testing activities on Controller Area Network (CAN) and ESC Electronic Control Unit (ECU) are carried out to compare the vehicle dynamic performance obtainable using serial production rather than customized control strategies, while maintaining the same hardware. The PV is also utilized to provide reverse engineering analysis about the implemented control strategy for the ESC working in serial production mode.

The dynamic model is built in Siemens Simcenter Amesim platform and simulates the performances on track of JUNO, a low energy demanding Urban Concept vehicle to take part in the Shell Eco-Marathon competition, in which the goal is to achieve the lowest fuel consumption in covering some laps of a racetrack, with limitations on the maximum race time. The model starts with the longitudinal dynamics, analysing all the factors that characterize the vehicle’s forward resistance, like aerodynamic forces, altimetry changes and rolling resistance. To improve the correlation between simulation and track performances, the model has been updated with the implementation of a Single-Track Model, including vehicle rotation around its roll axis, and a 3D representation of the racetrack, with an automatic trajectory following control implemented. This is crucial to characterise the vehicle’s lateral dynamics, which cannot be neglected in simulating its performances on track.