Title: Optimisation of the railway vehicle suspension system: an application of the genetic algorithms and the Pareto front method
Authors: Mohsen Mohammadi; Mohammad Ali Rezvani
Addresses: School of Railway Engineering, Iran University of Science and Technology, Narmak, Tehran 16846-13114, Iran ' School of Railway Engineering, Iran University of Science and Technology, Narmak, Tehran 16846-13114, Iran
Abstract: Railway vehicles rely on their suspension systems to enhance ride quality and ensure cargo safety. It is the aim of this research to optimise the design of such elements. This is performed in a procedure that imposes the least number of constraints and omits the need to weighing coefficients for the objective functions. By using the appropriate objective functions, the multi-objective optimisation problem is solved by genetic algorithms and system performance is optimised. Computer simulation is used to study the dynamics of the railway car in its vertical oscillations. Results are expressed in the framework of the optimal suspension performance curves. Verification of the proposed method involves simulation of a real case railway vehicle. It then compares the results from a MATLAB based simulation and the results from ADAMS/Rail engineering software simulation, for practical cases. The results prove that the proposed method is reliable and very adaptive to the suspension system specifications.
Keywords: railway vehicles; dynamic modelling; vehicle suspension; carbody flexibility; Pareto front curve; genetic algorithms; multi-objective optimisation; ride quality; cargo safety; simulation; vertical oscillation.
International Journal of Heavy Vehicle Systems, 2014 Vol.21 No.4, pp.328 - 350
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 15 Mar 2015 *