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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.

Active tire pressure control (ATPC) is an automatic central tire inflation system (CTIS), designed, prototyped, and tested at the Politecnico di Torino, which is aimed at improving the fuel consumption, safety, and drivability of passenger vehicles. The pneumatic layout of the system and the designed solution for on board integration are presented. The critical design choices are explained in detail and supported by experimental evidence. In particular, the results of experimental tests, including the characterizations of various pneumatic components in working conditions, have been exploited to obtain a design, which allows reliable performance of the system in a lightweight solution. The complete system has been tested to verify its dynamics, in terms of actuation time needed to obtain a desired pressure variation, starting from the current tire pressure, and to validate the design.

The selection and tuning of the Fuel Injection System (FIS) are among the most critical tasks for the automotive diesel engine design engineers. In fact, the injection strongly affects the combustion phenomena through which controlling a wide range of related issues such as pollutant emissions, combustion noise and fuel efficiency becomes feasible. In the scope of the engine design optimization, the simulation is an efficient tool in order to both predict the key performance parameters of the FIS, and to reduce the amount of experiments needed to reach the final product configuration. In this work a complete characterization of a solenoid ballistic injector for a Light-Duty Common Rail system was therefore implemented in a commercially available one-dimensional computational software called GT-SUITE. The main phenomena governing the injector operation were simulated by means of three sub-models (electro-magnetic, hydraulic and mechanical).

One of the key technologies for the improvement of the diesel engine thermal efficiency is the reduction of the engine heat transfer through the thermal insulation of the combustion chamber. This paper presents a numerical investigation on the effects of the combustion chamber insulation on the heat transfer, thermal efficiency and exhaust temperatures of a 1.6 l passenger car, turbo-charged diesel engine. First, the complete insulation of the engine components, like pistons, liner, firedeck and valves, has been simulated. This analysis has showed that the piston is the component with the greatest potential for the in-cylinder heat transfer reduction and for Brake Specific Fuel Consumption (BSFC) reduction, followed by firedeck, liner and valves. Afterwards, the study has been focused on the impact of different piston Thermal Barrier Coatings (TBCs) on heat transfer, performance and wall temperatures.

Nowadays, injection rate shaping and multi-pilot events can help to improve fuel efficiency, combustion noise and pollutant emissions in diesel engine, providing high flexibility in the shape of the injection that allows combustion process control. Different strategies can be used in order to obtain the required flexibility in the rate, such as very close pilot injections with almost zero Dwell Time or boot shaped injections with optional pilot injections. Modern Common-Rail Fuel Injection Systems (FIS) should be able to provide these innovative patterns to control the combustion phases intensity for optimal tradeoff between fuel consumption and emission levels.

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.

The sustainable use of energy and the reduction of pollutant emissions are main concerns of the automotive industry. In this context, Hybrid Electric Vehicles (HEVs) offer significant improvements in the efficiency of the propulsion system and allow advanced strategies to reduce pollutant and noise emissions. The paper presents the results of a simulation study that addresses the minimization of fuel consumption, NOx emissions and combustion noise of a medium-size passenger car. Such a vehicle has a parallel-hybrid diesel powertrain with a high-voltage belt alternator starter. The simulation reproduces real-driver behavior through a dynamic modeling approach and actuates an automatic power split between the Internal Combustion Engine (ICE) and the Electric Machine (EM). Typical characteristics of parallel hybrid technologies, such as Stop&Start, regenerative braking and electric power assistance, are implemented via an operating strategy that is based on the reduction of total losses.

In mathematical and mechanical modeling terms, automotive seating is characterized by boundary conditions at the nonlinear contact interfaces. These contact interfaces are subjected to vibro-impacts (slaps) and frictional slips. The slaps occur in contact interfaces at high amplitude vibrations, being characterized by very short duration, rapid dissipation of energy and large accelerations and decelerations. By considering friction in contact interface modeling, the simulation of the interaction between the driver and the vehicle seat becomes more realistic. Vibro-impacts and frictional slips can be simultaneously developed in a contact surface. The boundary conditions identification for a seat and a wide range of drivers' body types is performed using the concept of interference distance or penetration. The interference distance is introduced as an optimization problem. It is shown that the optimization problem provides robust solutions to minimum distance and interference problems.

The aim of this work is the assessment of the predictive capabilities of fast running models, obtained through an appropriate reduction and simplification process from detailed 1D fluid-dynamic models, for a turbocharged s.i. engine under highly transient operating conditions. Simulations results have been compared with experimental data for different types of models, ranging from fully detailed 1D fluid-dynamic models to map-based models, quantifying the degradation of the model accuracy and the reduction in the computational time for different kinds of driving cycles, from moderately transient such as the NEDC to highly dynamic such as the US06.

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.

Urban mobility represents one of the most critical global challenges nowadays. Several options regarding design and power sources technologies were recently proposed; among which electric and hybrid vehicles are quite successful to meet the increasingly restrictive environmental targets. This significant goal may affect the perceived vehicle comfort and drivability, especially in everyday urban scenarios. The purpose of this paper is to carry out a comparison in terms of comfort between vehicles belonging to different categories, but all designed for urban mobility: an electric 2-passenger quadricycle used during the demonstration phase of the European project STEVE, an internal combustion engine 2-passenger car (Smart Fortwo), an electric 4-passenger car (Bolloré Bluecar) and an internal combustion engine 4-passenger car (Fiat 500). Leading European car-sharing services use the last three car models.

This paper presents the methodology adopted by Politecnico di Torino Vehicle Dynamics Research Team to obtain objective indices for the evaluation of the comfort during the gear change process. Some test drivers and different passengers traveled on a test vehicle and assigned marks on the basis of their subjective feeling of comfort during the gearshifts. The comparison between the most significant subjective evaluations and the experimental values obtained by the instruments located on the vehicle is presented. As a consequence, some indices (based on physical parameters) to evaluate the efficiency and the comfort of the gearshift process are obtained. They are in good agreement with the subjective evaluations of the drivers and the passengers. The second part of the paper presents a driveline and vehicle model which was conceived to reproduce the phenomena experimented on the vehicle. The experimental validation of the model is presented.

This paper documents an extensive study aimed at a better understanding of the peculiarities and performance of crankshaft mounted gerotor pumps for IC engines lubrication. At different extents, the modelling, simulation and testing of a specific unit are all considered. More emphasis, at the modelling phase, is dedicated to the physical and mathematical description of the flow losses mechanisms; the often intricate aspects of kinematics being deliberately left aside. The pressure relief valve is analysed at a considerable extent as is the modelling of the working fluid, a typically aerated subsystem in such applications. Simulation is grounded on AMESim, a relatively novel tool in the fluid power domain, that proves effective and compliant with user deeds and objectives. Testing, at steady-state conditions, forms the basis for the pro!gressive tuning of the simulation model and provides significant insight into this type of volumetric pump.

In the automotive field the application of electric propulsion systems based on fuel cells requires a constant and continuing research of several optimized solutions, especially in terms of weight and size reduction. These key-factors tend to influence significantly the performance of the vehicle where the system is installed on. The main objective of the paper is to obtain breakthroughs in designing, manufacturing and assembling a fuel cell stack through the development of innovative metallic bipolar plates, that allows to set up high power density stacks, by lowering sensibly weight and size. The research activity carried out by the aforementioned authors is focused on the choice of suitable materials and the development of optimized tools, processes and techniques, in order to be able to move rapidly towards thinner bipolar plates, with new compact geometries that ensure the required stack output power.

The paper discusses a gearbox design method based on an optimization algorithm coupled to a fully integrated tool to draw 3D virtual models, in order to verify both functionality and design. The aim of this activity is to explain how the state of the art of the gear design may be implemented through an optimization software for the geometrical parameters selection of helical gears of a manual transmission, starting from torque and speed time histories, the required set of gear ratios and the material properties. This approach can be useful in order to use either the experimental acquisitions or the simulation results to verify or design all of the single gear pairs that compose a gearbox. Genetic algorithm methods are applied to solve the optimization problems of gears design, due to their capabilities of managing objective functions discontinuous, non-differentiable, stochastic, or highly non-linear.

In the frame of the space food production research activities conducted in the Thales Alenia Space Italia (TAS-I) Advanced Life Support Research and Development laboratory (RecycLAB, [6]), and with the contribution of a degree thesis developed in collaboration with the Politecnico of Torino, a rack-like facility for ground research on Life Support Systems based on Plants has been designed, developed, integrated, verified and tested in TAS-I. The new facility, called EDEN EPISODE 2, is a significant evolution of a previous TAS-I project (EDEN EPISODE 1) and takes benefit from other lower size TAS-I demonstrators (CUBE). It aims at realizing a completely closed and controlled environment for crop production, while a mobile lighting panel allows to maximize the delivered light in each phase of the plant life cycle. Hydroponic and aeroponic techniques have been implemented in the project for nutrient delivery to the plant roots.

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.

Scope of this work is the analysis of the energy consumed by lubricating gear pumps for automotive applications during a driving cycle. This paper presents the lumped parameter simulation model of gerotor lubricating pumps and the comparison between numerical outcomes and experimental results. The model evaluates the power required to drive the pump and the cumulative energy consumed in the driving cycle. The influence of temperature variations on leakage flows, viscous friction torque and lubricating circuit permeability is taken into account. The simulation model has been validated by means of a test rig for hydraulic pumps able to reproduce the typical speed, temperature and load profiles during a NEDC driving cycle. Experimental tests, performed on a crankshaft mounted pump for diesel engines, have confirmed a good matching with the simulation model predictions in terms of instantaneous quantities and overall energy consumption.