Abstract
For calibrating the vehicle model of a commercial vehicle dy- namics program a parameter estimation tool has been developed which relies on observations obtained from driving tests. The associated non- linear least-squares problem can be solved by means of mathematical op- timization algorithms most of them making use of first-order derivative information. While the complexity of the investigated vehicle dynam- ics program only allows the objective gradients to be approximated by means of finite differences, this approach enables significant savings in computational time when performing the additionally required evalua- tions of the objective function in parallel. The employed low-cost parallel computing platform which consists of a heterogeneous PC cluster is well suited for the needs of the automotive suppliers and industries employing vehicle dynamics simulations.
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References
Anonymous: veDYNA User’s Guide. TESIS DYNAware, München (1997)
Butz, T.: Parameter Identification in Vehicle Dynamics. Diploma Thesis, Zentrum Mathematik, Technische Universität München (1999)
Chucholowski, C, Vogel, M., von Stryk, O., Wolter, T.-M.: Real time simulation and online control for virtual test drives of cars. In: Bungartz, H.-J. et al. (eds.): High Performance Scientific and Engineering Computing. Lecture Notes in Computational Science and Engineering, Vol. 8. Springer-Verlag, Berlin (1999) 157–166
Gergeleit, M.: ONC RPC for Windows NT Homepage. World Wide Web, http://www.dcs.qmw.ac.uk/williams/nisgina-current/src/rpc110/oncrpc.htm (1996)
Gill, P.E., Murray, W., Saunders, M.A., Wright, M.H.: User’s Guide for NPSOL 5.0: A Fortran Package for Nonlinear Programming. Numerical Analysis Report 98-2, Department of Mathematics, University of California, San Diego (1998)
Gilmore, P.: IFFCO: Implicit Filtering for Constrained Optimization, User’s Guide. Technical Report CRSC-TR93-7, Center for Research in Scientific Computation, North Carolina State University, Raleigh (1993)
Moré, J.J.: The Levenberg-Marquardt algorithm: implementation and theory. In: Dold, A., Eckmann, B. (eds.): Numerical Analysis. Lecture Notes in Mathematics, Vol. 630. Springer-Verlag, Berlin Heidelberg (1978) 105–116
Nowak, U., Weimann, L.: A family of Newton codes for systems of highly nonlinear equations. Technical Report TR 91-10, ZIB, Berlin (1991)
Rill, G.: Simulation von Kraftfahrzeugen. Vieweg, Braunschweig (1994)
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Butz, T., von Stryk, O., Wolter, TM. (2000). A Parallel Optimization Scheme for Parameter Estimation in Motor Vehicle Dynamics. In: Bode, A., Ludwig, T., Karl, W., Wismüller, R. (eds) Euro-Par 2000 Parallel Processing. Euro-Par 2000. Lecture Notes in Computer Science, vol 1900. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44520-X_114
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DOI: https://doi.org/10.1007/3-540-44520-X_114
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