Wear/Comfort Pareto Optimisation of Bogie Suspension
Artikel i vetenskaplig tidskrift, 2016
Pareto optimisation of bogie suspension components is considered for a 50 degrees of freedom railway vehicle model to reduce wheel/rail contact wear and improve passenger ride comfort. Several operational scenarios including tracks with different curve radii ranging from very small radii up to straight tracks are considered for the analysis. In each case the maximum admissible speed is applied to the vehicle. Results of global sensitivity analysis of bogie dynamics with respect to suspension components are used to attenuate the number of input design parameters for optimisation. The most influential primary and secondary suspension elements on the bogie dynamics recognized by the sensitivity analysis are then categorized into two levels and the wear/comfort Pareto optimisation is accordingly accomplished in a multistep manner to improve the computational efficiency. The genetic algorithm is employed to perform the multiobjective optimisation. Two suspension system configurations are considered, a symmetric and an asymmetric one in which the primary or secondary suspension elements on the right and left hand sides of the vehicle are not the same. It is shown that the vehicle performance on curves can be significantly improved using the asymmetric suspension configuration. The Pareto optimized values of the design parameters achieved here guarantee wear reduction and comfort improvement for the underlying vehicle and can also be utilized in developing the reference vehicle models for design of bogie active suspension systems.
Pareto optimisation
genetic algorithm
wear
bogie suspension
comfort