Global sensitivity analysis and multiobjective optimization of bogie suspension
Paper in proceedings, 2016
Multiobjective optimization of nonlinear multibody systems with many degrees of freedom is a burdensome computational challenge.
A feasible practical methodology for global sensitivity analysis (GSA) of multibody systems with respect to design parameters is proposed based
on the multiplicative dimensional reduction method. The computational efficiency of optimization is significantly improved by restricting the
input design parameters only to those identified by the GSA. The methodology is applied for GSA of a railway vehicle dynamics with respect to
the bogie suspension characteristics. Several multiobjective optimization problems are then formulated and solved for a railway vehicle model
with 50 degrees of freedom using genetic algorithm. The results obtained yield practical information regarding the optimized bogie suspension
properties which improve the dynamics behaviour of the vehicle from various perspectives. The proposed algorithm can be used in design
optimization of nonlinear multibody systems with different applications.