Abstract

The objective of this study was to apply an innovative technique to manufacture a plastic automotive component to reduce its weight and costs, and guarantee its design was safe. A frontal impact sled test was simulated, and the damages to the occupant’s legs were assessed, with specific reference to the dashboard’s glove box. The replacement of the current glove box with a new component fabricated using additive manufacturing was analyzed to evaluate its passive safety performance in the event of an automobile accident. The materials analyzed were polyamide and polypropylene, both reinforced with 5% basalt. The stiffness of the system was previously characterized by reproducing a subsystem test. Subsequently, the same rating test performed by the Euro NCAP (New Car Assessment Program) was reproduced numerically, and the main biomechanical parameters required by the Euro NCAP were estimated for both the current and the additive production of the component.

Highlights

  • The use of lightweight designs and materials has become ubiquitous in the modern world

  • There has been a growing awareness of safety, and it has become a central theme in vehicle design

  • The rating test to numerically an automobile accident required a long calculation time to characterize the stiffness of its components, and proceed with optimization if necessary

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Summary

Introduction

The use of lightweight designs and materials has become ubiquitous in the modern world. The need for improved fuel economy has emphasized the use of lightweight materials and high-strength designs in automotive-component manufacturing. Automobile designers maintain high standards for performance, reliability, cost-effectiveness, competitiveness, and safety. Efficient numerical techniques have been developed to accurately simulate automobile accidents and limit the number of physical tests [1]. This has made it possible to hypothesize and analyze a high number of different configurations at the design stage and compare their different structural behaviors [2]. When correlating numerical and experimental data, after conducting simulations, it is possible to highlight the emerging criticalities and find the optimal solution

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