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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.

The acoustics of automotive intake and exhaust systems is typically modeled using linear acoustics or gas-dynamics simulation. These approaches are preferred during basic sound design in the early development stages due to their computational efficiency compared to complex 3D CFD and FEM solutions. The linear acoustic method reduces the component being modelled to an equivalent acoustic two-port transfer matrix which describes the acoustic characteristic of the muffler. Recently this method was used to create more detailed and more accurate models based on a network of 3D cells. As the typical automotive muffler includes perforated elements and sound absorptive material, this paper demonstrates the extension of the 3D linear acoustic network description of a muffler to include the aforementioned elements. The proposed method was then validated against experimental results from muffler systems with perforated elements and sound absorptive material.

Different hybrid powertrains for a European mid-size passenger car were evaluated in this paper through numerical simulation. Different degrees of hybridizations, from micro to mild hybrids, and different architectures and power sources management strategies were taken into account, in order to obtain a preliminary assessment of the potentialities of different hybrid systems for the European passenger car market. Both diesel and gasoline internal combustion engines were considered: a 1.6 dm₃ Common Rail turbocharged diesel, and a 1.4 dm₃ spark ignition turbocharged engine, equipped with an innovative Variable Valve Actuation system. Diesel hybrid powertrains, although being subject to NOx emissions constraints that could jeopardize their benefits, offered substantial advantages in comparison with gasoline hybrid powertrains. Potentialities for fuel consumption reductions up to 25% over the NEDC were highlighted, approaching the 2020 EU 95 g/km CO₂ target.

In spark-ignition engines, fluctuations of the in-cylinder pressure trace and the apparent rate of heat release are usually observed from one cycle to another. These Cycle-to-Cycle Variations (CCV) are affected by the early flame development and the subsequent flame front propagation. The CCV are responsible for engine performance (e.g. fuel consumption) and the knock behavior. The occurrence of the phenomena is unpredictable and the stochastic nature offers challenges in the optimization of engine control strategies. In the present work, CCV are analyzed in terms of their impact on the engine knock behavior and the related efficiency. Target is to estimate the possible fuel consumption savings in steady-state operation and in the drivecycle, when CCV are reduced. Since CCV are immanent on real engines, such a study can only be done by means of simulation.

Predicting the fuel economy capability of hybrid electric vehicle (HEV) powertrains by solving the related optimal control problem has been available for a few decades. Dynamic programming (DP) is one of the most popular techniques implemented to this end. Current research aims at integrating further powertrain modeling criteria that improve the fidelity level of the optimal HEV powertrain control behavior predicted by DP, thus corroborating the reliability of the fuel economy assessment. Dedicated methodologies need further development to avoid the curse of dimensionality which is typically associated to DP when increasing the number of control and state variables considered. This paper aims at considerably reducing the overall computational effort required by DP for HEVs by removing the state term associated to the battery state-of-charge (SOC).

The application of computational methods for the development of the whole engine-vehicle system has been evaluated in this paper, to highlight the potential of computer simulation techniques applied to the analysis of engine-vehicle matching. First, engine performance was simulated using a one-dimensional fluid dynamic code, and predicted data were compared to experimental results, to assess the accuracy of the engine computer model not only as far as gross engine performance parameters are concerned, but also for the prediction of pressure values at several locations inside the engine. The simulation was also extended to the whole engine operating range, including part-load operating conditions. Afterwards, a vehicle simulation code was employed, to predict vehicle performance and fuel consumption.

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.

Feed-forward low-throughput models have been developed to predict MFB50 and to control SOI in order to achieve a specific MFB50 target for diesel engines. The models have been assessed on a GMPT-E Euro 5 diesel engine, installed at the dynamic test bench at ICEAL-PT (Internal Combustion Engine Advanced Laboratory at the Politecnico di Torino) and applied to both steady state and transient engine operating conditions. MFB50 indicates the crank angle at which 50% of the fuel mass fraction has burned, and is currently used extensively in control algorithms to optimize combustion phasing in diesel engines in real-time. MFB50 is generally used in closed-loop combustion control applications, where it is calculated by the engine control unit, cycle-by-cycle and cylinder by-cylinder, on the basis of the measured in-cylinder pressure trace, and is adjusted in order to reduce the fuel consumption, combustion noise and engine-out emissions.

The hydrogen and fuel cell power based technologies that are rapidly emerging can be exploited to start a new generation of propulsion systems for light aircraft and small commuter aircraft. Different studies were undertaken in recent years on fuel cells in aeronautics. Boeing Research & Technology Centre (Madrid) successfully flew its converted Super Dimona in 2008 relying on a fuel cell based system. DLR flew in July 2009 with the motor-glider Antares powered by fuel cells. The goal of the ENFICA-FC project (ENvironmentally Friendly Inter City Aircraft powered by Fuel Cells - European Commission funded project coordinated by Prof. Giulio Romeo) was to develop and validate new concepts of fuel cell based power systems for more/all electric aircrafts belonging to a “inter-city” segment of the market.

Nowadays stringent emission regulations are pushing towards new air management strategies like LP-EGR and HP/LP mix both for passenger car and heavy duty applications, increasing the engine control complexity. Within a project in collaboration between Kohler Engines EMEA, Politecnico di Torino, Ricardo and Denso to exploit the potential of EGR-Only technologies, a 3.4 liters KDI 3404 was equipped with a two stage turbocharging system, an extremely high pressure FIS and a low pressure EGR system. The LP-EGR system works in a closed loop control with an intake oxygen sensor actuating two valves: an EGR valve placed downstream of the EGR cooler that regulates the flow area of the bypass between the exhaust line and the intake line, and an exhaust flap to generate enough backpressure to recirculate the needed EGR rate to cut the NOx emission without a specific aftertreatment device.

Beside hard facts as performance, emissions and fuel consumption especially the brand specific attributes such as styling and sound are very emotional, unique selling prepositions. To develop these emotional characters, within the given boundary conditions of the future pass-by regulation, it is necessary to define them at the very beginning of the project and to follow a consequent development process. The following paper shows examples of motorcycle NVH development work on noise cleaning and sound engineering using a hybrid development process combining front loading, simulation and testing. One of the discussed solutions is the investigation of a piston pin offset in combination with a crankshaft offset for the reduction of friction. The optimization of piston slap noise as a result of the piston secondary motion was performed by simulation. As another example a simulation based development was performed for the exhaust system layout.

The paper deals with the design and manufacturing of a McPherson suspension arm made from short glass fiber reinforced polyamide (PA66). The design of the arm and the design of the molds have been made jointly. According to Industry 4.0 paradigms, a full digitalization of both the product and process has been performed. Since the mechanical behavior of the suspension arm strongly depends on constraints which are difficult to be modelled, a simpler structure with well-defined mechanical constraints has been developed. By means of such simple structure, the model for the behavior of the material has been validated. Since the suspension arm is a hybrid structure, the associated simple structure is hybrid as well, featuring a metal sheet with over-molded polymer. The issues referring to material flow, material to material contact, weld lines, fatigue strength, high and low temperature behavior, creep, dynamic strength have been investigated on the simple structure.

A methodology for an efficient failure prediction of automotive steel wheels during fatigue experimental tests is proposed. The strategy joins the CDTire simulative package effectiveness to a specific wheel finite element model in order to deeply monitor the stress distribution among the component to predict damage. The numerical model acts as a Software-in-the-loop and it is calibrated with experimental data. The developed tool, called VirtualWheel, can be applied for the optimisation of design reducing prototyping and experimental test costs in the development phase. In the first section, the failure criterion is selected. In the second one, the conversion of hardware test-rig into virtual model is described in detail by focusing on critical aspects of finite element modelling. In conclusion, failure prediction is compared with experimental test results.

In this paper a novel approach to mimic through numerical simulation Cycle-to-Cycle Variations (CCV) of the combustion process of Spark Ignition (SI) engines is described. The proposed methodology allows to reproduce the variability in combustion which is responsible for knock occurrence and thus to replicate the stochastic behavior of this abnormal combustion phenomenon. On the basis of the analysis of a comprehensive database of experimental data collected on a typical European downsized and turbocharged SI engine, the proposed approach was demonstrated to be capable to replicate in the simulation process the same percentage of knocking cycles experimentally measured in light-knock conditions, after a proper calibration of the Kinetics-Fit (KF), a new phenomenological knock model which was recently developed by Gamma Technologies.

The electrification of the powertrain is a prerequisite to meet future fuel consumption limits, while the internal combustion engine (ICE) will remain a key element of most production volume relevant powertrain concepts. High volume applications will be covered by electrified powertrains. The range will include parallel hybrids, 48V- or High voltage Mild- or Full hybrids, up to Serial hybrids. In the first configurations the ICE is the main propulsion, requiring the whole engine speed and load range including the transient operation. At serial hybrid applications the vehicle is generally electrically driven, the ICE provides power to drive the generator, either exclusively or supporting a battery charging concept. As the ICE is not mechanically coupled to the drive train, a reduction of the operating range and thus a partial simplification of the ICE is achievable.

A new test bench has been set up and equipped in order to analyze the air mean motion and turbulence quantities in the combustion system of an automotive diesel engine with one helicoidal intake duct and a conical type in-piston bowl. A sophisticated HWA technique employing single- and dual-sensor probes was applied to the in-cylinder flow investigation under motored conditions. The anemometric probe was also operated as a thermometric sensor. An analytical-numerical procedure, based on the heat balance equations for both anemometric and thermometric wires, was refined and applied to compute the gas velocity from the anemometer output signal. The gas property influence, the thermometric sensor lag and the prong temperature effects were taken into account with this procedure. The in-cylinder velocity data were reduced using both a cycle-resolved approach and the conventional ensemble-averaging procedure, in order to separate the mean flow from the fluctuating motion.

In the last decades, the locomotion of wheeled and tracked vehicles on soft soils has been widely investigated due to the large interest in planetary, agricultural, and military applications. The development of a tire-soft soil contact model which accurately represents the micro and macro-scale interactions plays a crucial role for the performance assessment in off-road conditions since vehicle traction and handling are strongly influenced by the soil characteristics. In this framework, the analysis of realistic operative conditions turns out to be a challenging research target. In this research work, a semi-empirical model describing the interaction between a tire and homogeneous and fine-grained soils is developed in Matlab/Simulink. The stress distribution and the resulting forces at the contact patch are based on well-known terramechanics theories, such as pressure-sinkage Bekker’s approach and Mohr-Coulomb’s failure criterion.

One of the major issues coming out from low temperature fuel cells concerns the production of water vapor as a chemical reaction (between hydrogen and oxygen) by-product and its consequent condensation (at certain operating conditions), determining the presence of an amount of liquid water affecting the performance of the fuel cell stack: the production and the quantity of liquid water are strictly influenced by boundaries and power output conditions. Starting from this point, this work focuses on collecting all the required information available in literature and defining a suitable CFD model able to predict the production of liquid water within the fuel cell, while at the same time localizing it and determining the consequences on the PEM cell performances.

Computational Fluid Dynamics is a powerful instrument for PEM fuel cell systems development, testing and optimization. Considering the complication due to the multiple physical phenomena involved in the cell's operations, a good understanding of the micro-scale fluidic behavior in boundary layers is recommended: pressure drop along the reactants gas channels and the cooling channels has a sensible effect on parasite load in fuel cell systems (i.e. the power absorbed by the pump supplying the gases), as well as an important role in thermal transport. A correct thermal and fluid dynamic boundary layer prediction on the channel walls and the other contact surface with porous layers requires usually a dense finite element volumes discretization near wall, especially if laminar flows occur: therefore, the boundary layer computational cost tends to be the major one.

In the present work, a scalable simulation methodology is presented that enables the assessment of the impact of SI-engine cycle-to-cycle combustion variations on fuel consumption and hence CO2 emissions on three different levels of modeling depth: in-cylinder, steady-state engine and transient engine and vehicle simulation. On the detailed engine combustion chamber level, a 3D-CFD approach is used to study the impact of the turbulent in-cylinder flow on the cycle-resolved flame propagation characteristics. On engine level, cycle-to-cycle combustion variations are assessed regarding their impact on indicated mean effective pressure, aiming at estimating the possible fuel consumption savings when cyclic variations are minimized. Finally, on the vehicle system level, a combined real-time engine approach with crank-angle resolved cylinder is used to assess the potential fuel consumption savings for different vehicle drivecycle conditions.