基于灰色關聯(lián)的電動汽車傳動系統(tǒng)速比多目標優(yōu)化

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中圖分類號：U469.72 文獻標志碼：B 文章編號：1671-5276（2025）03-0276-05

Abstract：Acording totheautomotivetheory，themotor，batteryandtransmisionsystemparametersarecalculated，the simulationanalysismodelisestablishedbasedonSightand Cruise，thesingle-objectiveoptimizationof thetransmissionsystem spedratioisperformedbythemulti-islandgeneticalgorithm，andtheweightcoeficientofeachsingletargetinthemultiobjectiveoptimizatoniscalculatedbythegracoelationmethd.ThmultibjectiveoptimiationofteNSGA-Ialgoriis applied to compare with the multi objective optimization metod of the empirical weight coeficient.The results show that the maximum climbing degree of the optimization method based on grey correlation is decreased by 4.36% ，the energy consumption of 100 kilometers is decreased by 2.33% ，and the overalloptimization effect is better than that of the multi-objective optimization method based on empirical determination of weight coefficient.

Keywords：electricvehicles；speedratioof powersystem；greycorelation；multi-objectiveoptimization;geneticalgorithm

0 引言

電動汽車能夠顯著提升能量轉化效率，但是電動汽車動力電機輸出的動力通過傳動系統(tǒng)傳遞到車輪，動力系統(tǒng)的匹配設計與優(yōu)化分析對其動力性和經濟性有較大影響[2-3]

在對純電動汽車動力系統(tǒng)進行優(yōu)化的時候，一般考慮最大爬坡度、加速時間、最高車速、百公里電耗中的一個或者多個指標作為目標進行優(yōu)化[4-6]。（剩余5673字）