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The current trend towards an increasing electrification of road vehicles brings to life a whole series of unprecedent design issues. Among these, the ageing process that affects the lifetime of lithium-ion based energy storage systems is of particular importance since it turns out to be extremely sensitive to the variation of battery operating conditions normally occurring especially in hybrid electric vehicles (HEVs). This paper aims at analyzing the impact of operating conditions on the predicted lifetime of a parallel-through-the-road plug-in HEV battery both from thermal and ageing perspectives. The retained HEV powertrain architecture is presented first and modeled, and the related energy management system is implemented. Dedicated numerical models are also discussed for the high-voltage battery pack that allow predicting its thermal behavior and cyclic ageing.

The battery of a vehicle with an electrified powertrain (Hybrid Electric Vehicle or Battery Electric Vehicle), is required to operate with highly dynamic power outputs, both for charging and discharging operation. Consequently, the battery current varies within an extensive range during operation and the battery temperature also changes. In some cases, the relationship between the current flow and the change in the electrical energy stored seems to be affected by inefficiencies, in literature described as current losses, and nonlinearities, typically associated with the complex chemical and physical processes taking place in the battery. When calculating the vehicle electrical energy consumption over a trip, the change in the electrical energy stored at vehicle-level has to be taken into account. This quantity, what we could call the vehicle electricity balance, is typically obtained through a time-based integration of the battery current of all the vehicle batteries during operation.

Hybrid electric vehicle (HEV) powertrains are characterized by a complex design environment as a result of both the large number of possible layouts and the need for dedicated energy management strategies. When selecting the most suitable hybrid powertrain architecture at an early design stage of HEVs, engineers usually focus solely on fuel economy (directly linked to tailpipe emissions) and vehicle drivability performance. However, high voltage batteries are a crucial component of HEVs as well in terms of performance and cost. This paper introduces a multitarget assessment framework for HEV powertrain architectures which considers both fuel economy and battery lifetime. A multi-objective formulation of dynamic programming is initially presented as an off-line optimal HEV energy management strategy capable of predicting both fuel economy performance and battery lifetime of HEV powertrain layout options.

Gearbox behavior is strictly affected by gears, shaft, bearings and casing stiffnesses. As a matter of fact, their contribution to gear dynamics is fundamental for mechanical transmissions design. In this paper a semi-analytical model developed for the estimation of the dynamic behavior of two mating gears is presented and tested on two case studies. Starting with the estimation of the Static Transmission Error, intended as the difference between the theoretical and actual angular position between the two mating gears, the dynamic behavior of the mating elements is estimated by means of a Dynamic Model. The Dynamic Model takes into account the gears, the contact between teeth exchanging loads and the other mechanical elements reduced by means of a DOF reduction technique. Based on the block-oriented approach, Dynamic Model allows the user to easily manage the complexity of the system with further or less elements by adding or removing DOFs.

One of the first steps in powertrain design is to assess its best performance and consumption in a virtual phase. Regarding hybrid electric vehicles (HEVs), it is important to define the best mode profile through a cycle in order to maximize fuel economy. To assist in that task, several off-line optimization algorithms were developed, with Dynamic Programming (DP) being the most common one. The DP algorithm generates the control actions that will result in the most optimal fuel economy of the powertrain for a known driving cycle. Although this method results in the global optimum behavior, the DP tool comes with a high computational cost. The charge-sustaining requirement and the necessity of capturing extremely small variations in the battery state of charge (SOC) makes this state vector an enormous variable. As things move fast in the industry, a rapid tool with the same performance is required.

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.

Experimental Design methodologies have been applied in conjunction with objective functions for the optimization of the internal geometry of a rear muffler of a subcompact car equipped with a 1.4 liters displacement s.i. turbocharged engine. The muffler also features an innovative variable geometry design. The definition of an objective function summarising the silencing capability of the muffler has been driving the optimization process with the aim to reduce the tailpipe noise while maintaining acceptable pressure losses and complying with severe space constraints. Design of Experiments techniques for the reduction of experimental plans have been shown to be extremely effective to find out the optimum values of the design parameters, allowing a remarkable reduction of the time required by the design process in comparison with full factorial designs.

In the powertrain technology, designers must be careful on oil pan design in order to obtain the best noise, vibration and harshness (NVH) performance. This is a great issue for the automotive design because they affect the passengers' comfort. In order to reduce vibration and radiated noise in powertrain assembly, oil pan is one of the most critical components. The high stiffness of the oil pan permits to move up the natural modes of the component and, as a consequence, reduce the sound emission of the component itself. In addition, the optimized shape of the component allows the increase of natural frequency values of the engine assembly. The aim of this study is the development of a methodology to increase the oil pan stiffness starting from a sketch of the component and adding material where it is needed. The methodology is tested on a series of different models: they have the same geometry but different materials.

A numerical model for simulating a Common Rail Piezo Indirect Acting fuel injection-system under steady state as well as transient operating conditions was developed using a commercial code. A 1D flow model of the main hydraulic system components, including the rail, the rail to injector connecting pipe and the injector, was applied in order to predict the influence of the injector layout and of each part of the hydraulic circuit on the injection system performance. The numerical code was validated through the comparison of the numerical results with experimental data obtained on a high performance test bench of the Moehwald-Bosch MEP2000/ CA4000 type. The developed injection-system mathematical model was applied to the analysis of transient flows in the hydraulic circuit paying specific attention to the fluid dynamics internal to the injector.

Electric scooters are suited to mobility in zones with environmental traffic limitations, and particularly for city centers with very poor room for parking. Aim of this paper is the illustration of the performance that can be obtained from a purposely designed electric scooter. The features of the main components of the scooter driveline: battery package, converter, motor and control will be described.

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.

This paper deals with the ground testing of the technological demonstrator of the innovative remotely controlled ETF airship1. The testing activities are intended to validate the flight control system of the ETF, which is based on the thrust vectoring technology and represents one of the major innovations of the ETF design, together with the airship architecture. A research team of the Aeronautical and Space Department of the Polytechnic of Turin, in collaboration with Nautilus, a small Italian private company, has been working since a few years on the ETF (Elettra Twin Flyers). This airship is remotely-piloted, with high maneuverability capabilities and good operative features also in adverse atmospheric conditions2. The Nautilus new concept airship features architecture and appropriate command system, which should enable the vehicle to maneuver in forward, backward and sideward flight and hovering with any heading, both in normal and severe wind conditions.

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 paper presents the main results of a study on the simulation of energy efficient management of on-board electric and thermal systems for a medium-size passenger vehicle featuring a parallel-hybrid diesel powertrain with a high-voltage belt alternator starter. A set of advanced technologies has been considered on the basis of very aggressive fuel economy targets: base-engine downsizing and friction reduction, combustion optimization, active thermal management, enhanced aftertreatment and downspeeding. Mild-hybridization has also been added with the goal of supporting the downsized/downspeeded engine performance, performing energy recuperation during coasting phases and enabling smooth stop/start and acceleration. The simulation has implemented a dynamic response to the required velocity and manual gear shift profiles in order to reproduce real-driver behavior and has actuated an automatic power split between the Internal Combustion Engine (ICE) and the Electric Machine (EM).

Given the growing concern for environmental issues, the automotive industry is working more deeply on the development of innovative technologies that reduce gas emissions and fuel consumption. Many car manufacturers have identified hybrid electric vehicles (HEV) and fuel cell vehicles as the most promising solutions alternatives. IDRApegasus is a fuel cell hydrogen vehicle developed at the Politecnico of Turin. It participated at the Shell Eco-marathon Europe in Rotterdam (Netherlands) from 17-19 May 2012, a competition for low energy consumption vehicles and also an educational project that joins the value of sustainable development with a vehicle that will use the smallest amount of fuel and produce the lowest emissions possible.

The necessity for further reductions of in-cylinder pollutant formation and the opportunity to minimize engine development and testing times highlight the need of engine thermodynamic cycle simulation tools that are able to accurately predict the effects of fuel, design and operating variables on engine performance. In order to set up reliable codes for indicated cycle simulation in SI engines, an accurate prediction of heat release is required, which, in turn, involves the evaluation of in-cylinder turbulence generation and flame-turbulence interaction. This is generally pursued by the application of a combustion fractal model coupled with semi-empirical correlations of available geometrical and thermodynamical mass-averaged quantities. However, the currently available correlations generally show an unsatisfactory capability to predict the effects of flame-turbulence interaction on burning speed under the overall flame propagation interval.

Meticulous design of the energy management control algorithm is required to exploit all fuel-saving potentials of a hybrid electric vehicle. Equivalent consumption minimization strategy is a well-known representative of on-line strategies that can give near-optimal solutions without knowing the future driving tasks. In this context, this paper aims to propose an adaptive real-time equivalent consumption minimization strategy for a multi-mode hybrid electric powertrain. With the help of road recognition and vehicle speed prediction techniques, future driving conditions can be predicted over a certain horizon. Based on the predicted power demand, the optimal equivalence factor is calculated in advance by using bisection method and implemented for the upcoming driving period. In such a way, the equivalence factor is updated periodically to achieve charge sustaining operation and optimality.

Monitoring and preserving state-of-health of high-voltage battery packs in electrified road vehicles currently represents an open and growing research topic. When predicting high-voltage battery lifetime, most current literature assumes a uniform temperature distribution among the different cells of the pack. Nevertheless, temperature has been demonstrated having a key impact on cell lifetime, and different cells of the same battery pack typically exhibit different temperature profiles over time, e.g. due to their position within the pack. Following these considerations, this paper aims at assessing the effect of temperature distribution on the predicted lifetime of cells belonging to the same battery pack. To this end, a throughput-based numerical cell ageing model is firstly selected due to its reasonable compromise between accuracy and computational efficiency.

The paper presents experimental and theoretical investigations on a shaft mounted gerotor lubricating pump aimed at reducing radiated noise at high engine speed. Effects of noise generation identified as main sources are the fluid borne noise (FBN) that originates in unsteady flow and related pressure fluctuations and structure borne noise (SBN) as a result of pressure transients occurring internally, which cause vibrations of the pump case. To clarify the onset of large delivery pressure fluctuations detected at high pump speed (in excess of 4000 rpm), and validate simulation results (AMESim environment), experimental and theoretical studies have been performed.

An integrated theoretical and experimental investigation was carried out in order to evaluate the effects that the pump delivery-valve assembly can produce on the performance of a pump-line-nozzle fuel-injection system with a distributor-type pump for automotive diesel engines. Four distinct delivery valves, one constant-pressure valve, one reflux-hole and two relief-volume valves, were separately fitted to the pump and for each configuration of the delivery assembly the system behavior was analyzed under full-load steady-state operations in a wide pump angular-speed range. Fuel injection-rate as well as local pressure time-histories were investigated, paying specific attention to the occurrence and temporal evolution of cavitation phenomena in the pressure pipe and injector nozzle, after the valve closure. The flow across the delivery-valve assembly was theoretically examined in order to ascertain any instability sources as possible causes of cyclic fluctuations.