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Traditional CACC systems utilize inter-vehicle wireless communication to maintain minimal yet safe inter-vehicle distances, thereby improving traffic efficiency. However, introducing communication delays generates system uncertainties that jeopardize string stability, a crucial requirement for robust CACC performance. To address these issues, we introduce a decentralized Model Predictive Control (MPC) approach that incorporates Kalman Filters and state predictors to counteract the uncertainties posed by noise and communication delays. We validate our approach through MATLAB Simulink simulations, using stochastic and mathematical models to capture vehicular dynamics, Wi-Fi communication errors, and sensor noises. In addition, we explore the application of a Reinforcement Learning (RL)-based algorithm to compare its merits and limitations against our decentralized MPC controller, considering factors like feasibility and reliability.

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.

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.

Composite materials are a natural choice for automotive applications where mechanical performance and lightweight are required. Nevertheless, attention should be directed to the defects into the material. This paper presents the building up of a Structural Health Monitoring system based on a piezoelectric transducers network: a continuous data system acquisition has been carried out in order to detect the presence of faults inside the analyzed structure. A piezoceramic patch has been coupled to a host structure in composite, to characterize the acquisition and the transmission of a wave signal on the material. The importance of this advanced technology research and the positive results obtained in the case study constitute the starting point for future application of piezoelectric-based Structural Health Monitoring systems over real industrial components.

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.

Nowadays the increasing demand for sustainable mobility has fostered the introduction of innovative propulsion systems also in the public transport sector in order to achieve a significant reduction of pollutant emissions in highly congested urban areas. Within this context this paper describes the development of the HYBUS, an environmental friendly hybrid bus for on-road urban transportation, which was jointly carried out by Pininfarina and Politecnico di Torino in the framework of the AMPERE project. The first prototype of the bus was built by integrating an innovative hybrid propulsion system featuring a plug-in series architecture into the chassis of an old IVECO 490 TURBOCITY. The bus is 12 meters long and has a capacity of up to 116 passengers in the original layout. The project relied on a modular approach where the powertrain could be easily customized for size and power depending on the specific application.

It is well known that backpressure is one of the important parameters to be minimised during the exhaust system development. Unfortunately, during the first phases of an engineering process of a new engine, engine prototypes are not available yet. Due to this the exhaust system backpressure is generally evaluated using simulation software, and/or measuring the backpressure by a flow rig test at room temperature. Goal of this paper is to compare exhaust backpressure results obtained respectively: i) at the room temperature flow rig; ii) at the engine dyno bench; iii) by simulation with one of the most common 1D fluidodynamics simulation tool (Gt-Power). A correlation of the three different techniques is presented.

This paper presents a technique for extracting modal parameters of a linear multi degree of freedom system in the frequency domain. The roots of the technique are the well known rational fraction polynomials method but emphasis is given to the application to output-only data in the form of cross-spectral density functions. A discussion is presented on the possibility of achieving reliable results also for structures undergoing multiple input excitations. Numerical stability of the technique is obtained by properly scaling both the frequency and the cross-spectrum axes. Good performance of the method are shown for numerical examples and for a test case on an actual structure.

Automotive cabin filters of the “combo” type are intended to remove both aerosols and gaseous contaminants from air entering the climate control system. We analyze the performance of two filters of this type, using published values for the concentration of gaseous contaminants found in highway and street traffic. Using existing expressions for the performance of activated carbons, including the effects of contaminant concentration, flow rate and carbon bed depth, we calculate retentivity and breakthrough time for benzene and carbon tetrachloride at street-level concentrations. The calculated factors are compared to published test data on similar filters.

The paper presents geometric, kinematic and fluid-dynamic modelling of variable displacement vane pumps for low pressure applications in internal combustion engines lubrication. All these fundamental aspects are integrated in a simulation environment and form the core of a design tool leading to the assessment of performance, critical issues, related influences and possible solutions in a well grounded engineering support to decision.