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Computational Analysis of Body Stiffness Influence on the Dynamics of Light Commercial Vehicles

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Advances in Mechanism and Machine Science (IFToMM WC 2019)

Abstract

This paper presents the computational analysis of the frame flexibility influence on the dynamics of light commercial vehicles. The goal is deter-mine the handling performance influence of a lightweight aluminum rear frame pre-design and its comparison with the original steel body behaviour. A biblio-graphical review points out FEM and Multibody computational integration as the best way of approaching the problem and a theoretical analysis highlights the main handling related issues originated from the flexibility of the body. Simplified FEM models are constructed using Hypermesh in order to obtain the static torsional stiffness and the vibration modes and frequencies below 100 Hz. This reduced model is included in the Multi-body simulation in Adams/Car, where four different full-vehicle models are built – rigid and flexible body versions of the original vehicle and of the aluminum design. To draw the conclusions, these models are submitted to three different dynamic maneuvers: constant radius curve, step steering, and pothole encountering. The results point out the importance of the body flexibility inclusion in the vehicular dynamic studies of light commercial vehicles and about the changes required to the aluminum frame in order to assure better dynamic performance of the vehicle.

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Acknowledgements

The authors wish to acknowledge: Vehicle Engineering and Design for the opportunity and active support during all the activity. Special acknowledgements to Ing. Giovanni and Marco Salvi, and to Ing. Carlo Avataneo.

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Correspondence to Henrique de Carvalho Pinheiro .

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de Carvalho Pinheiro, H., Messana, A., Sisca, L., Ferraris, A., Airale, A.G., Carello, M. (2019). Computational Analysis of Body Stiffness Influence on the Dynamics of Light Commercial Vehicles. In: Uhl, T. (eds) Advances in Mechanism and Machine Science. IFToMM WC 2019. Mechanisms and Machine Science, vol 73. Springer, Cham. https://doi.org/10.1007/978-3-030-20131-9_307

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