Optimal design of high-speed vehicle suspension system based on parameter sensitivity stratification
WU Fu
DU Zeyang
LI Zhongxue
YANG Xijuan
JIANG Pengmin
Abstract：[Objective]To address the issues of numerous parameters and time-consuming calculations in the optimization of high-speed vehicle suspension systems,a layered optimization design based on the parameter sensitivity stratification was proposed.[Methods]Firstly,a dynamic simulation model of a single high-speed vehicle was constructed and validated for pragmatic.The optimal Latin hypercube sampling method was utilized to evenly extract sample points for calculating dynamic responses in the model,and a surrogate model was employed to replace the time-consuming dynamic model in order to enhance optimization efficiency.Secondly,after determining the optimization variable through sensitivity analysis,the variable was stratified.For the two stratified variables,the nearest neighbor cultivation transplantation algorithm and the downhill simplex method were used to advance the optimization process.Finally,the optimization results were compared with the original solution and those obtained from the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ).[Results]The results demonstrate that the optimization respectively reduces the nonlinear critical speed and derailment coefficient by 14.584%and 9.615%,surpassing the NSGA-Ⅱ in comprehensive optimization rate and reducing the design iterations,thereby improving the dynamic performance of high-speed vehicles and validating the feasibility of the optimization method.
Keywords：Dynamic performanceMulti-objective optimizationSuspension parameterParameter sensitivity stratifica-tionSurrogate model
Publication Date：2026-03-15
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：9( 87-95 )