Sensibilidad paramétrica de un automóvil con polinomios de caos

It is interesting to analyze the parameter sensitivity of mathematical models that describe physical systems, and it deserves particular attention the sensitivity study of models with uncertainty in the parameter values. Global sensitivity takes into account the entire range of parameter uncertainty because it considers the parameters as random variables. This paper presents the global sensitivity analysis in frequency of a parametric mathematical model of lateral dynamics of a vehicle model, with an approach based on the polynomial chaos expansion of the model response. This technique allows to easily represent the system as a stochastic model, where the parameters become random variables that vary according to their uncertainty. The stochastic model should be a very close approximation of the original model.

[1]  N. Wiener.  The Homogeneous Chaos , 1938 .

[2]  Eric Walter,et al.  Identification of Parametric Models: from Experimental Data , 1997 .

[3]  K. Shuler,et al.  Nonlinear sensitivity analysis of multiparameter model systems , 1977 .

[4]  Eduardo Haro Sandoval,et al.  Estimación de los Parámetros Físicos de un Automóvil , 2008 .

[5]  R. Ghanem,et al.  Stochastic Finite Elements: A Spectral Approach , 1990 .

[6]  Ilya M. Sobol,et al.  Sensitivity Estimates for Nonlinear Mathematical Models , 1993 .

[7]  A. Saltelli,et al.  A quantitative model-independent method for global sensitivity analysis of model output , 1999 .

[8]  Jeroen A. S. Witteveen,et al.  Modeling Arbitrary Uncertainties Using Gram-Schmidt Polynomial Chaos , 2006 .

[9]  J. D. Morrison,et al.  Evaluating prediction uncertainty in simulation models , 1999 .

[10]  Stefano Tarantola,et al.  Application of global sensitivity analysis of model output to building thermal simulations , 2008 .

[11]  Floriane Anstett-Collin,et al.  Sensitivity study of dynamic systems using polynomial chaos , 2012, Reliab. Eng. Syst. Saf..

[12]  Julien Jacques,et al.  Sensitivity analysis in presence of model uncertainty and correlated inputs , 2006, Reliab. Eng. Syst. Saf..

[13]  D. Xiu,et al.  Modeling uncertainty in flow simulations via generalized polynomial chaos , 2003 .

[14]  Olivier P. Le Maître,et al.  Polynomial chaos expansion for sensitivity analysis , 2009, Reliab. Eng. Syst. Saf..

[15]  John Red-Horse,et al.  Propagation of probabilistic uncertainty in complex physical systems using a stochastic finite element approach , 1999 .

[16]  Bruno Sudret,et al.  Global sensitivity analysis using polynomial chaos expansions , 2008, Reliab. Eng. Syst. Saf..

[17]  A. Saltelli,et al.  Importance measures in global sensitivity analysis of nonlinear models , 1996 .