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Virtual Optimisation of Passive Safety Performance Using D.O.E. Techniques
CAR2005_FISITA/CAR20051001-FinalPaper

Authors

Ianniello Gerardo - Elasis S.C.p.A., Italy
Monacelli Gennaro - Elasis S.C.p.A., Italy
Petrella Vincenzo - Elasis S.C.p.A., Italy

Abstract

KEYWORDS

Passive safety, biomechanics, virtual analysis, multibody approach, optimisation

ABSTRACT

Passive safety is one of the main performances of a new car. It is well known that it is very expensive and time consuming to achieve the targets of this performance using only experimental tests. This work deals with a new methodology to find the optimal configuration of the main parameters that influence the biomechanical performance in high speed frontal crash. This method is based on the integration of experimental tests, numerical simulation and D.O.E. (Design Of Experiment) techniques. An experimental frontal impact test has been modelled in Madymo with a mixed approach multibody and FEM. The numerical model consists of passenger compartment and dummy. The seat, the dashboard, the driving wheel and the restraints systems (safety belts and airbags) are modelled in each detail while the pulse comes from experimental test. The model has been refined comparing numerical and experimental results; this process has driven to a numerical model that represents the physical phenomenon and has indicated the main parameters that influence the biomechanical performance. The best set up of these parameters has been found applying DOE techniques to the numerical model correlated with the experimental results: using the results of a calculation plan a system response model has been formulated; it is a mathematical model that connects the output (biomechanical parameters) to the input parameters. The system response model has been used to find the configuration that maximize the biomechanical performance. The relevant aspect of this methodology is to allow the designer to find those values of the design variables which bring the output objective variables nearest to a chosen target using only one experimental test, reducing costs and time to develop a new car.

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