Lightweight design of electric drive axle housing with reliability analysis
LI Dongqi
GAO Zhibin
Abstract：[Objective]To address the lightweight issue of electric drive axle housing,a specialized lightweight design method based on an approximate model and combinatorial optimization algorithm was proposed.Furthermore,the introduction of the 6σ reliability optimization theory aimed to enhance the stability of the axle housing.[Methods]Firstly,the design variables that have a significant impact on the performance of the axle housing were selected through sensitivity analysis.Secondly,a radial basis function(RBF)neural network approximation model of the axle housing was constructed based on test design data,followed by deterministic multi-objective optimization using a combination algorithm of the second-generation non-dominated sorting genetic algorithm(NSGA-Ⅱ)and the non-linear programming by quadratic Lagrangian(NLPQL).Finally,considering the influence of uncertain factors on the performance of the axle housing,6σ reliability analysis theory was introduced for reliability optimization design based on RBF neural network approximation model.[Results]The results indicate a 6.9%reduction in mass after optimized design,along with improved reliability in axle housing performance meeting 6σ standards.
Keywords：Electric drive axle housingLightweight designMulti-objective optimizationApproximation modelCom-bination algorithm
Publication Date：2025-10-31
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：9( 53-61 )