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The paper presents a method for the indoor testing of road vehicle suspension systems. A suspension is positioned on a rotating drum which is located in the Laboratory for the Safety of Transport at Politecnico di Milano. Special six-axis load cells have been designed and used for measuring the forces/moments acting at each suspension-chassis joints. The forces/moments, wheel accelerations, displacements are measured up to 100 Hz. Two different types of test can be performed. The tire/wheel unbalance effect on the suspension system behavior (Vibration and Harshness, VH) has been analyzed by testing the suspension system from zero to the vehicle maximum speed on a flat surface and by monitoring the forces transmitted to the chassis. In the second kind of test, the suspension system has been excited as the wheel passes over different cleats fixed on the drum.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

In recent years, the increase of gasoline fuel injection pressure is a way to improve thermal efficiency and lower engine-out emissions in GDI homogenous combustion concept. The challenge of controlling particulate formation as well in mass and number concentrations imposed by emissions regulations can be pursued improving the mixture preparation process and avoiding mixture inhomogeneity with ultra-high injection pressure values up to 100 MPa. The increase of the fuel injection pressure in GDI homogeneous systems meets the demand for increased injector static flow, while simultaneously improves the spray atomization and mixing characteristics with consequent better combustion performance. Few studies quantify the effects of high injection pressure on transient gasoline spray evolution. The aim of this work was to simulate with OpenFOAM the spray morphology of a commercial gasoline injected in a constant volume vessel by a prototypal GDI injector.

The electrochemical performance of a lithium-ion battery is strongly affected by the temperature. During charge and discharge cycles, batteries are subjected to an increment of temperature that can accelerate aging and loss of efficiency if critical values are reached. Knowing the thermal parameters that affect the heat exchange between the battery surface and the surrounding environment (air, cooling fins, plates, etc…) is fundamental to their thermal management. In this work, thermal imaging is applied to a laminated lithium-polymers battery as a non-invasive temperature-indication method. Measurements are taken during the discharge phase and the following cooling down until the battery reaches the ambient temperature. The 2d images are used to analyze the homogeneity of the temperature distribution on the battery surface. Then, experimental results are coupled with mathematical correlations.

The common realization of the necessity to reduce the use of mineral sources is promoting the use of alternative fuels. Big efforts are being made to replace petroleum derivatives in the internal combustion engines (ICEs). For this purpose it is mandatory to evaluate the behavior of non-conventional fuels in the ICEs. The optical diagnostics have proven to be a powerful tool to analyze the processes that take place inside the engine. In particular, 2d imaging in the infrared range can reveal new details about the effect of the fuel properties since this technique is still not very common. In this work, a comparison between commercial diesel fuel and two non-conventional fuels has been made in an optically accessible diesel engine. The non-conventional fuels are: the first generation biofuel Rapeseed Methyl Ester (RME) and an experimental blend of diesel and a fuel with high glycerol content (HG).

In the last decades numerical simulations have become reliable tools for the design and the optimization of silencers for internal combustion engines. Different approaches, ranging from simple 1D models to detailed 3D models, are nowadays commonly applied in the engine development process, with the aim to predict the acoustic behavior of intake and exhaust systems. However, the acoustic analysis is usually performed under the hypothesis of infinite stiffness of the silencer walls. This assumption, which can be regarded as reasonable for most of the applications, can lose validity if low wall thickness are considered. This consideration is even more significant if the recent trends in the automotive industry are taken into account: in fact, the increasing attention to the weight of the vehicle has lead to a general reduction of the thickness of the metal sheets, due also to the adoption of high-strength steels, making the vibration of the components a non negligible issue.

The modeling of fuel sprays under well-characterized conditions relevant for heavy-duty Diesel engine applications, allows for detailed analyses of individual phenomena aimed at improving emission formation and fuel consumption. However, the complexity of a reacting fuel spray under heavy-duty conditions currently prohibits direct simulation. Using a systematic approach, we extrapolate available spray models to the desired conditions without inclusion of chemical reactions. For validation, experimental techniques are utilized to characterize inert sprays of n-dodecane in a high-pressure, high-temperature (900 K) constant volume vessel with full optical access. The liquid fuel spray is studied using high-speed diffused back-illumination for conditions with different densities (22.8 and 40 kg/m3) and injection pressures (150, 80 and 160 MPa), using a 0.205-mm orifice diameter nozzle.

Isooctane sprays from a multi-hole GDI injector were investigated in a constant volume chamber by means of high speed imaging techniques. The tests were performed under inert conditions (nitrogen), at temperatures and densities ranging between representative operating conditions of late injection, flash boiling and early injection in a GDI engine. The global parameters of the sprays were obtained by processing Schlieren, Shadowgraph, DBI and Mie-scattering images through an in-house image processing method. Thus, the boundaries of the spray vapor phase can be easily detected with great accuracy, regardless of whether Schlieren or the less sensitive shadowgraph imaging is used. Furthermore, the boundaries of the liquid phase were also obtained from shadowgraph images and compared with those obtained through DBI and scattering. The results show that the signature of the liquid phase in a shadowgraph image can be distinguished from that of the vaporized fuel.

Autonomous ground vehicles can use a variety of techniques to navigate the environment and deduce their motion and location from sensory inputs. Visual Odometry can provide a means for an autonomous vehicle to gain orientation and position information from camera images recording frames as the vehicle moves. This is especially useful when global positioning system (GPS) information is unavailable, or wheel encoder measurements are unreliable. Feature-based visual odometry algorithms extract corner points from image frames, thus detecting patterns of feature point movement over time. From this information, it is possible to estimate the camera, i.e., the vehicle’s motion. Visual odometry has its own set of challenges, such as detecting an insufficient number of points, poor camera setup, and fast passing objects interrupting the scene. This paper investigates the effects of various disturbances on visual odometry.

The influence of the inertia properties (mass, centre of gravity location, and inertia tensor) on the dynamic behaviour of the engine-gearbox system of a car is studied in this paper, devoting particular attention to drivability and comfort. The vibration amplitudes and the natural frequencies of the engine-gearbox system have been considered. Additionally, the loads transmitted to the car body have been taken into account. Both the experimental and the theoretical simulations confirmed that the engine-gearbox vibrations in the range 10 - 15 Hz are particularly sensitive to slight variation of the inertia properties. The effects on engine-gearbox vibrations due to half-axles, exhaust system, pipes and inner engine-gearbox fluids have been highlighted.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

The flow field resulting from injecting a gas jet into a crossflow confined in a narrow square duct has been studied under steady regime using schlieren imaging and laser Doppler velocimetry (LDV). This transparent duct is intended to simulate the intake port of an internal combustion engine fueled by gaseous mixture, and the jet is issued from a round nozzle. The schlieren images show that the relative small size of the duct would confine the development of the transverse jet, and the interaction among jet and sidewalls strongly influences the mixing process between jet and crossflow. The mean velocity and turbulence fields have been studied in detail through LDV measurements, at both center plane and several cross sections. The well-known flow feature formed by a counter rotating vortex pair (CVP) has been observed, which starts to appear at the jet exit section and persists far downstream contributing to enhancing mixing process.

The numerical reconstruction of the liquid jet generated by a multi-hole injector, operating in flash-boiling conditions, has been developed by means of a Eulerian- Lagrangian CFD code and validated thanks to experimental data collected with schlieren and Mie scattering imaging techniques. The model has been tested with different injection parameters in order to recreate various possible engine thermodynamic conditions. The work carried out is framed in the growing interest present around the gasoline direct-injection systems (GDI). Such technology has been recognized as an effective way to achieve better engine performance and reduced pollutant emissions. High-pressure injectors operating in flashing conditions are demonstrating many advantages in the applications for GDI engines providing a better fuel atomization, a better mixing with the air, a consequent more efficient combustion and, finally, reduced tailpipe emissions.

The aim of this paper is the experimental investigation of the effect of direct fuel injection on the combustion process and pollutant formation in a spark ignition (SI) two-wheel engine. The engine is a 250cc single cylinder, four-stroke spark-ignition firstly equipped with a four-valve PFI head and then with GDI one operating with European commercial gasoline and Bio-ethanol. It is equipped with a wide sapphire window in the bottom of the chamber and quartz cylinder. In the combustion chamber, optical techniques based on 2D-digital imaging were used to follow the injection and flame propagation and spectroscopic measurements were carried out in order to evaluate the main radical species. Radical species such as OH and CH were detected and used to follow the chemical phenomena related to the fuel quality. Measurements were carried out at different engine speeds and combustion strategies based on different injection pressures.

This paper is focused on the development and application of a CFD methodology that can be applied to predict the fuel-air mixing process in stratified charge, sparkignition engines. The Eulerian-Lagrangian approach was used to model the spray evolution together with a liquid film model that properly takes into account its effects on the fuel-air mixing process into account. However, numerical simulation of stratified combustion in SI engines is a very challenging task for CFD modeling, due to the complex interaction of different physical phenomena involving turbulent, reacting and multiphase flows evolving inside a moving geometry. Hence, for a proper assessment of the different sub-models involved a detailed set of experimental optical data is required. To this end, a large experimental database was built by the authors.

The present paper deals with a comprehensive analysis of the knocking phenomenon through experiments and numerical simulations. Conventional and non-conventional measurements are performed on a 4-stroke, 4-cylinder, turbocharged GDI engine. The engine exhibits optical accesses to the combustion chamber. Imaging in the UV-visible range is carried out by means of a high spatial and temporal resolution camera through an endoscopic system and a transparent window in the piston head. This last is modified to allow the view of the whole combustion chamber almost until the cylinder walls, to include the so-called eng-gas zones. Optical data are correlated to in-cylinder pressure-based indicated analyses in a cycle resolved approach.

Data decomposition techniques have become a standard approach for the analysis of 2D imaging data originating from optically accessible internal combustion engines. In particular, the method of Proper Orthogonal Decomposition (POD) has proven to be a valuable tool for the evaluation of cycle-to-cycle variability based on luminous combustion imaging and particle image velocimetry (PIV) measurements. POD basically permits to characterize the dominant structures of the process under consideration. Recently, an alternative procedure based on Independent Component Analysis (ICA) has been introduced in the engine field. Unlike POD, the method of ICA identifies the patterns corresponding to physical processes that are statistically independent. In this work, a Group-ICA approach is applied to 2D cycle-resolved images of the luminosity emitted by the combustion process. The analysis is meant to characterize cyclic variability of a port fuel injection spark ignition (PFI SI) engine.

The objective of this study was to identify and gain an understanding of the origins of noise in a commercial excavator cab. This paper presents the results of two different tests that were used to characterize the vibration and acoustic characteristics of the excavator cab. The first test was done in an effort to characterize the vibration properties of the cab panels and their associated contribution to the noise level inside the cab. The second set, of tests, was designed to address the contribution of the external airborne noise produced by the engine and hydraulic pump to the overall interior noise. This paper describes the test procedures used to obtain the data for the signature analysis, operational deflection shapes (ODS), and sound diagnosis analysis. It also contains a discussion of the analysis results and an inside look into the possible contributors of key frequencies to the interior noise in the excavator cab.

Sensory jury testing was utilized to characterize vibration levels perceived by the operator, with respect to levels measured using instrumentation, in order to develop a tool for the evaluation of vibration at the operator interfaces. Details of the jury testing and jury data processing method are highlighted as well as the refinement of vibration characterization for a specific application. The vibration at user interface locations of both snowmobiles and ATVs was measured along with subjective feedback from a panel of jurists. Statistical analysis was performed on the jury data to provide both a qualitative and quantitative number to represent the opinion of the jury. Correlations were developed between the measured levels of vibration and the opinions of the jury. Finally, a set of correlation functions suitable for design predictions was developed.