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Recently sustainability has become a priority for industry production. This issue is even more valid for the automotive sector, where Original Equipment Manufacturers have to address the environmental protection in addition to the traditional design issues. Against this background, many research and industry advancements are concentrated in the development of lightweight car components through the application of new materials and manufacturing technologies. The paper deals with an innovative lightweight design solution for the bumper system module of a C-segment gasoline car. The study has been developed within the Affordable LIght-weight Automobiles AlliaNCE (ALLIANCE) project, funded by the Horizon 2020 framework programme of the European Commission. A rear crash management system module, that is currently in series production and mainly consists of conventional steel and aluminum materials, is re-engineered making use of ultra high strength 7000 series alloys.

A rapidly shifting market and increasingly stringent environmental regulations require the automotive industry to produce more efficient low-emission Electric Vehicles (EVs). Regenerative braking has proven to be a major contributor to both objectives, enabling the charging of the batteries during braking and a reduction of the load and wear of the brake pads. The optimal sizing of such systems requires the availability of good simulation models to improve their performance and reliability at all stages of the vehicle design. This enables the designer to study both the integration of the braking system with the full vehicle equipment and the interactions between electrical and mechanical braking strategies. This paper presents a generic simulation framework for the identification of thermal and wear behaviour of a mechanical braking system, based on a lumped parameter approach.

During the last few decades, the European regulations concerning CO2 emissions and vehicle recyclability/recoverability rates are leading OEMs to develop and apply several technological strategies to increase environmental performances of vehicles. In this context, the lightweighting is a key concern because it effectively contributes to reduce vehicle mass, fuel consumption and CO2 emissions during the operation stage of vehicle. The research advancements are enhancing the applicability of a diverse set of innovative materials (e.g. polymers, bio-composites) to different vehicle assemblies and so the mass reduction with the same mechanical performances. This paper deals with the implementation of LCA methodological approach in the design phase of components of Magneti Marelli® allowing a wider environmental conscious related to the usage of innovative materials and related manufacturing processes.

Powered Two-Wheelers (PTW) control is more complex than any other motorized vehicle control, in particular during emergency events, such as panic braking or last second swerving. For standard PTW, a common cause of accident in these situations is the loss of stability due to braking maneuvers. It is worth noting that for PTW the loss of stability means a high probability of fall, especially while cornering. Accordingly, the aim of this study is to propose a fall detection algorithm for PTW performing maneuvers leading to potential instability. The algorithm is composed of a number of parameters, named RISKi, able to detect potential fall events, critical for PTW safety. This fall detection methodology was developed to alert an advanced riding assistance system in order to produce proper counteractions against the imminent fall.

In the study of new solutions for motorcycle passive safety, FE models of full-scale crash tests play a strategic role. The most important issue in the development process of FE models is their reliability to reproduce real crash tests. To help the engineering in the validation phase, a sensitivity analysis of a FE model for motorcycle-car crash tests is carried-out. The aim of this study is to investigate the model response subjected to variations of specific input parameters. The DOE is performed generating a list of simulations (each one composed by a unique combination of 8 parameters) through Latin Hypercube Sampling. The outputs monitored are the Head Injury Criterion (HIC) and Neck Injury Criteria (Nij). The analysis of the results is performed using scatter plots and linear regression curves to identify the parameters that have major impact on the outputs and to assess the type of dependency (linear or non-linear).

In the last few years, some of the computational limitations imposed by the classical Boundary Element Methods (BEM) have been overtaken thanks to the Fast Multipole BEM (FMBEM) which allows solving large acoustic models much faster. Nevertheless, as the BEM, the FMBEM suffers from non-uniqueness of the solution and the exterior prediction is polluted by fictitious resonances. Since the FMBEM is based on an iterative solver, not only the accuracy is degraded. In fact, the number of iterations to the convergence, in correspondence of a fictitious resonance, is larger and the total computational time increases. Applying the impedance condition over the whole inner boundary allows to completely damp fictitious resonances with a drastic increase of computational cost. Nevertheless, when the condition is applied on a well-chosen percentage of elements, the accurate solution is obtained even faster.