Multi-objective optimization of mobile charging vehicle frame based on improved MOGA
HUANG Junming
LI Jiaqi
YE Lei
LI Longjie
QIN Pinpin
HUANG Wei
Abstract：[Objective]Aiming at the problems that the mobile charging vehicle frame has remarkable heavy-load characteristics and variable loads under multiple working conditions,and the traditional multi-objective genetic algorithm(MOGA)has insufficient global optimization ability and is prone to fall into local optimum,to solve the collaborative optimization problem of frame lightweight design and dynamic-static performance improvement,a multi-objective optimization method for vehicle frames based on an improved multi-objective genetic algorithm was proposed.[Methods]Firstly,load information of key bearing parts of the frame was obtained through multi-condition real vehicle tests,and an implicit parametric finite element model of the frame was established to complete dynamic-static performance analysis and clarify structural response characteristics.Secondly,optimal Latin hypercube sampling was adopted to obtain sample points,and a high-precision proxy model was constructed to quantify the influence law of design variables on frame stress and mass.Then,an adaptive crossover strategy pool was introduced into the traditional multi-objective genetic algorithm to improve the global search ability of the algorithm,and a mathematical model for multi-objective optimization of the frame was established.Finally,the entropy-technique for order preference by similarity to ideal solution(TOPSIS)method was used to select the optimal scheme from the Pareto solution set,and the performance verification of the optimized scheme was completed.[Results]The results show that the improved multi-objective genetic algorithm has significantly better convergence and global optimization ability;the mass of the optimized frame is reduced by 9.44％,the maximum stress and maximum displacement under four typical working conditions are decreased,and the first-order natural frequency is increased to 92.247 Hz.The dynamic and static performance of the frame is improved while lightweight is realized,which provides reference for the optimization design of similar bearing structures.
Keywords：Mobile charging vehicleFrameMulti-objective optimizationImproved MOGAEntropy-TOPSIS method
Publication Date：2026-08-15
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：11( 10-20 )