Research Papers

Optimal Design of Experiments for Estimating Parameters of a Vehicle Dynamics Simulation Model

[+] Author and Article Information
Torsten Butz1

 TESIS DYNAware GmbH, Baierbrunner Straβe 15, 81379 München, Germanyt.butz@tesis.de

Bernd Simeon

Zentrum Mathematik, Technische Universität München, Boltzmannstraβe 3, 85748 Garching, Germanysimeon@ma.tum.de

Markus Stadler

 Bain & Company Switzerland, Inc., 8037 Zurich, Switzerlandmarkus.stadler@bain.com


Corresponding author.

J. Comput. Nonlinear Dynam 5(3), 031011 (Jun 15, 2010) (7 pages) doi:10.1115/1.4001391 History: Received March 12, 2009; Revised December 03, 2009; Published June 15, 2010; Online June 15, 2010

The calibration of complex simulation models for vehicle component and controller development usually relies on numerical methods. In this contribution, a two-level optimization scheme for estimating unknown model parameters in a commercial real-time capable vehicle dynamics program is proposed. In order to increase the reliability of the model coefficients estimated from reference data, the measuring test is improved by methods for the optimal design of experiments. Specifically, the control variables of the experimental setup are adjusted in such a way as to maximize the sensitivity of the parameters in demand with respect to the objective function. The numerical results show that this two-level optimization scheme is capable of estimating the parameters of a multibody suspension model.

Copyright © 2010 by American Society of Mechanical Engineers
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Figure 1

Geometrical interpretation of the optimal experimental design criteria

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Figure 2

Iterative refinement of the surrogate model (22)

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Figure 3

Multilink suspension model with rubber bushings in DYNA4

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Figure 4

Sensitivities of the estimated bushing elasticities with the initial excitation

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Figure 5

Characteristics of the D- and A-criteria for the optimal experimental design problem

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Figure 6

Sensitivities of the estimated bushing elasticities with the optimized excitation




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