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Handling and Primary Ride Comfort Development in Early Design Stage by Means of 1D Modeling Approach and Multi Attribute Optimization Process

[+] Author Affiliations
Stefano Alneri, Paolo di Carlo

LMS International, Torino, Italy

Alessandro Toso, Stijn Donders

LMS International, Heverlee, Belgium

Paper No. IMECE2011-62679, pp. 155-167; 13 pages
doi:10.1115/IMECE2011-62679
From:
  • ASME 2011 International Mechanical Engineering Congress and Exposition
  • Volume 9: Transportation Systems; Safety Engineering, Risk Analysis and Reliability Methods; Applied Stochastic Optimization, Uncertainty and Probability
  • Denver, Colorado, USA, November 11–17, 2011
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5495-2
  • Copyright © 2011 by ASME

abstract

Today the automotive market is ever more competitive and vehicles must satisfy the requirements of the customers in all respects: handling, comfort, acoustics, fuel economy, etc. Therefore OEMs have to launch innovative products in a short development timeline: the time to market (TTM) of new vehicles has continually decreased and nowadays the developing process of a new car is completed in less years than in the past. This scenario emphasizes the role of CAE in the vehicle design engineering design and the necessity of exploiting its potentialities, in order to shorten the TTM and to reduce the impact of experimental tests on it. In this context a step-by-step approach with multi-physics 1D environment such as LMS Imagine. Lab AMESim is proposed in order to monitor vehicle performances in all the design stages, thanks to the employment of models with increasing complexity. In addition the ultimate step can be employed for performing a multi attribute optimization on vehicle performance metrics in order to find the best attributes balancing and to pass the preliminary recommendations to the design with a considerable time-saving respect to 3D MBS models. This paper briefly describes the process for building 1D models with LMS Imagine.Lab AMESim and moreover it shows the definition of a multi attribute optimization algorithm in terms of handling performances with the most complex model.

Copyright © 2011 by ASME

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