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The aim of this work is to apply an innovative adaptive ℒ1 techniques to control flutter phenomena affecting highly flexible wings and to evaluate the efficiency of this control algorithm and architecture by performing the following tasks: i) adaptation and analysis of an existing simplified nonlinear plunging/pitching 2D aeroelastic model accounting for structural nonlinearities and a quasi-steady aerodynamics capable of describing flutter and post-flutter limit cycle oscillations, ii) implement the ℒ1 adaptive control on the developed aeroelastic system to perform initial control testing and evaluate the sensitivity to system parameters, and iii) perform model validation and calibration by comparing the performance of the proposed control strategy with an adaptive back-stepping algorithm. The effectiveness and robustness of the ℒ1 adaptive control in flutter and post-flutter suppression is demonstrated.

In Motorsports the understanding of the real engine performance within a complete circuit lap is a crucial topic. On the basis of the telemetry data the engineers are able to monitor this performance and try to adapt the engine to the vehicle's and race track's characteristics and driver's needs. However, quite often the telemetry is the sole analysis instrument for the Engine-Vehicle-Driver (EVD) system and it has no prediction capability. The engine optimization for best lap-time or best fuel economy is therefore a topic which is not trivial to solve, without the aid of suitable, reliable and predictive engineering tools. A complete EVD model was therefore built in a GT-SUITE™ environment for a Motorsport racing car (STCC-VW-Scirocco) equipped with a Compressed Natural Gas (CNG) turbocharged S.I. engine and calibrated on the basis of telemetry and test bench data.

Vehicle dynamics estimation has been the subject of study for some years now. If on-board vehicle control systems can be provided with information such as side slip angle, lateral force etc. then stability of the vehicle can be improved. To estimate these dynamic variables different observers have been used e.g., sliding mode, fuzzy logic, neural networks etc. In this article the authors propose an extended Kalman filter to estimate vehicle side slip angle. Roll angle is estimated using vertical loads as input. First, a linear Kalman filter is used to filter out the vertical forces and estimate roll angle. This information is then used to estimate the vehicle side slip angle. To take into account the nonlinearities concerning lateral vehicle dynamics, Pacejka magic formula is used to model lateral forces. Estimated results are then compared with simulations, showing good accuracy.

Active Roll Control (ARC) is one of the most promising active systems to improve vehicle comfort and handling. This paper describes the simulation based procedure adopted to conceive a double-channel Active Roll Control system, characterized by the hydraulic actuation of the stabilizer bars of a sedan. The first part of the paper presents the vehicle model adopted for this activity. It is Base Model Simulator (BMS), the 14 Degrees-of-Freedom vehicle model by Politecnico di Torino. It was validated through road tests. Then the paper describes the development of the control algorithm adopted to improve the roll dynamics of the vehicle. The implemented control algorithm is characterized by a first subsystem, capable of obtaining the desired values of body roll angle as a function of lateral acceleration during semi-stationary maneuvers.

The effects of using neat FAME (Fatty Acid Methyl Ester) in a modern small displacement passenger car diesel engine have been evaluated in this paper. In particular the effects on engine performance at full load with standard (i.e., without any special tuning) ECU calibration were analyzed, highlighting some issues in the low end torque due to the lower exhaust gas temperatures at the turbine inlet, which caused a remarkable decrease of the available boost, with a substantial decrease of the engine torque output, far beyond the expected engine derating due to the lower LHV of the fuel. However, further tests carried out after ECU recalibration, showed that the same torque levels measured under diesel operation can be obtained with neat biodiesel too, thus highlighting the potential for maintaining the same level of performance.

A method for estimating the sideslip angle of a Formula SAE vehicle with torque vectoring is presented. Torque vectoring introduces large tire longitudinal forces which lead to a reduction of the tire lateral forces. A novel tire model is utilized to represent this reduction of the lateral forces. The estimation is realized using an extended Kalman filter which takes in standard sensor measurements. The developed algorithm is tested by simulating slalom and figure eight maneuvers on a validated VI-CarRealTime vehicle model. Results indicate that the algorithm is able to estimate the sideslip angle of the vehicle reliably on a high friction surface track.

Simulation is becoming the fundamental tool to design the main components of a vehicle. The paper describes the shock absorber model which was implemented by the Vehicle Dynamics Research Team of Politecnico di Torino. It is a modular model which can be adopted both for mono-tube and twin-tube shock absorbers. It can be used at different levels of approximation, as a function of the kind of user and his/her targets. The main data which have to be inserted in the model are fluid properties, the basic dimensions of the component and the characteristics of the orifices of the shock absorber. An experimental test bench was conceived to obtain the diagrams plotting flow rate through an orifice of a shock absorber versus the pressure drop between input and output ports. The test rig and the procedure to perform the experimental tests and insert the results in the shock absorber model are described in detail.

Vehicle dynamics is a fundamental part of vehicle performance. It combines functional requirements (i.e. road safety) with emotional content (“fun to drive”, “comfort”): this balance is what characterizes the car manufacturer (OEM) driving DNA. To reach the customer requirements on Ride & Handling, integration of CAE and testing is mandatory. Beside of cutting costs and time, simulation helps to break down vehicle requirements to component level. On chassis, the damper is the most important component, contributing to define the character of the vehicle, and it is defined late, during tuning, mainly by experienced drivers. Usually 1D lookup tables Force vs. Velocity, generated from tests like the standard VDA, are not able to describe the full behavior of the damper: different dampers display the same Force vs. Velocity curve but they can give different feeling to the driver.

An experimental investigation was performed on a turbocharged spark-ignition 4-cylinder production engine fuelled with natural gas and with two blends of natural gas and hydrogen (15% and 25% in volume of H₂). The engine was purposely designed to give optimal performance when running on CNG. The first part of the experimental campaign was carried out at MBT timing under stoichiometric conditions: load sweeps at constant engine speed and speed sweeps at constant load were performed. Afterwards, spark advance sweeps and relative air/fuel ratio sweeps were acquired at constant engine speed and load. The three fuels were compared in terms of performance (fuel conversion efficiency, brake specific fuel consumption, brake specific energy consumption and indicated mean effective pressure) and brake specific emissions (THC, NOx, CO).

Given the ever-increasing concern about environmental issues, the automotive industry is focusing on the development of innovative technologies that allow reduction of gas emissions and fuel consumption. Over the last few years, Hybrid Electric Vehicles (HEV) and Fuel Cell Vehicles have been developed as the most promising alternative solutions for many car manufacturers. Although fuel cells are considered as the best technology to have zero emission, the impact on infrastructure for a large-scale deployment is not yet solved. For this reason, HEV represent a valid shorter-term alternative that guarantees drastic emissions reduction and reduced fuel consumption with a much lower infrastructural impact. This paper reports the results obtained by the optimization of the emissions and fuel performances of a hybrid electric city vehicle for urban transportation named XAM (eXtreme Automotive Mobility). In order to optimize these performances, a 1D model of the vehicle has been created.

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.

In the face of growing concerns about environmental sustainability and urban congestion, the integration of eco-driving strategies has emerged as a pivotal solution in the field of the urban transportation sector. This study explores the potential benefits of a CAV functioning as a virtual eco-driving controller in an urban traffic scenario with a group of following human-driven vehicles. A computationally inexpensive and realistic powertrain model and energy management system of the Chrysler Pacifica PHEV are developed with the field experiment data and integrated into a forward-looking vehicle simulator to implement and validate an eco-driving speed planning and energy management strategy assuming longitudinal automation. The eco-driving algorithm determines the optimal vehicle speed profile and energy management strategy.

Sustainable and energy-efficient consumption is a main concern in contemporary society. Driven by more stringent international requirements, automobile manufacturers have shifted the focus of development into new technologies such as Hybrid Electric Vehicles (HEVs). These powertrains offer significant improvements in the efficiency of the propulsion system compared to conventional vehicles, but they also lead to higher complexities in the design process and in the control strategy. In order to obtain an optimum powertrain configuration, each component has to be laid out considering the best powertrain efficiency. With such a perspective, a simulation study was performed for the purpose of minimizing well-to-wheel CO2 emissions of a city car through electrification. Three different innovative systems, a Series Hybrid Electric Vehicle (SHEV), a Mixed Hybrid Electric Vehicle (MHEV) and a Battery Electric Vehicle (BEV) were compared to a conventional one.

Electric vehicles comprising multiple motors allow the individual wheel torque allocation, i.e. torque-vectoring. Powertrain configurations with multiple motors provide additional degree of freedom to improve system level efficiencies while ensuring handling performances and active safety. However, most of the works available on this topic do not simultaneously optimize both vehicle dynamic performance and energy efficiency while considering the real-time implementability of the controller. In this work, a new and systematic approach in designing, modeling, and simulating the main layers of a torque-vectoring control framework is introduced. The high level control combines the actions of an adaptive Linear Quadratic Regulator (A-LQR) and of a feedforward controller, to shape the steady-state and transient vehicle response by generating the reference yaw moment. A novel energy efficient torque allocation method is proposed as a low level controller.

Ride comfort assessment is undoubtedly related to the interaction between the vehicle tires and the road surface. Indeed, the road profile represents the typical input for tire vertical load estimation in durability analysis and for active/semi-active suspension controller design. However, the road profile evaluation through direct experimental measurements involves long test time and excessive cost required by professional instrumentations to detect the road irregularities with sufficient accuracy. An alternative is shifting attention towards efficient and robust algorithms for indirect road profile evaluation. The object of this work aims at providing road profile estimation starting from vehicle dynamics measurements, through accessible and traditional sensors, with the application of a linear Kalman filter algorithm.

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).

The innovative highly flexible wings made of extremely light structures, yet still capable of carrying a considerable amount of non- structural weights, requires significant effort in structural simulations. The complexity involved in such design demands for simplified mathematical tools based on appropriate nonlinear structural schemes combined with reduced order models capable of predicting accurately their aero-structural behaviour. The model presented in this paper is based on a consistent nonlinear beam-wise scheme, capable of simulating the unconventional aeroelastic behaviour of flexible composite wings. The partial differential equations describing the wing dynamics are expanded up to the third order and can be used to explore the effect of static deflection imposed by external trim, the effect of gust loads and the one of nonlinear aerodynamic stall.

The Atmospheric Revitalization System (ARS) provides carbon dioxide removal, trace contaminant control, and gas constituent analysis. In this field, the interest of RecycLAB [5], the TAS-I Advanced Live Support Research & Development laboratory is directed to trace gas contaminants removal and monitoring. During manned space mission, the decontamination of cabin or rack air after contingency events such as fire or pyrolysis is a priority for the crew safety. In this paper, basic zeolites, obtained by impregnation of common zeolites with a basic oxide, are used to remove acid gas contaminants from air stream. A multi-functional system, able to accommodate reactors of different shape, characteristics and set-up, is used at this purpose. This breadboard, called ZEUS (Zeolites for an Environmental-control Unit in Space), is made of AISI 316L stainless steel and consists of a closed loop, in which the inner volume is completely isolated from the external environment.

Aim of this work is the development of a lumped parameters simulation model of single-vane vacuum pumps for pneumatically actuated brake boosters. Kinematic and fluid-dynamic models are integrated in a simulation environment to create a tool aimed at evaluating the vacuum pump performance and at guiding the designer during the prototype development. The paper describes extensively the mathematical model, the time domain simulation and experimental analyses performed on a camshaft mounted unit. Great emphasis is placed on the evaluation of the geometric quantities of the control volumes into which the vacuum pump has been divided. For each control volume the mass and energy conservation equations lead to the determination of the instantaneous pressure. The volume of each variable chamber and the respective angular derivative are calculated as function of the shaft position starting from the stator track profile supplied as a generic closed polyline.

As technology evolves, the number of sensors and available data on vehicles grow exponentially. In this context, it is essential to use sensors for monitoring key components, increasing safety and reliability, and gathering data useful for mechanical dimensioning and control systems. This paper presents an application of strain-gauged bolts on brake calipers fixation of two electric vehicles. With this approach it was possible to evaluate the loads applied to the brake pads fixation zone and correlate them with braking behavior, therefore gaining insights on braking conditions and system state for an improved braking function control. The goal of the study is analyzing the strengths and limitations of the method and proposing developments to deploy it in real applications. This is particularly important and novel for electric vehicles, where powertrains can create positive/negative torques and generate complex interactions with braking system.