基于移动粒子半隐式法(MPS)电动汽车减速器最佳润滑油量分析

Analysis of Optimum Lubricant Quantity of Electric Vehicle Reducer based on Moving Particle Semi-implicit Method(MPS)

在分析某电动汽车减速器内元件的产热与传热过程的基础上,建立了基于AMEsim软件某电动汽车减速器热网络仿真模型,假设在充分润滑情况下,完成了高温高负荷不同车速工况条件下的减速器热平衡仿真。应用移动粒子半隐式法(MPS)分析了不同润滑油油量时减速箱的搅油流场,在此基础上,对减速器热网络模型中的对流换热热阻模块进行修正,分析得出减速器最佳润滑油油量。修正结果表明,电动汽车减速器在高温高负荷工况下,较少的润滑油油量会导致减速器齿轮系处于欠润滑状态,致使齿面温度较高。将热网络法与移动粒子半隐式法(MPS)相结合,为电动汽车减速器润滑效果分析提供了一种新方法。

Based on the analysis of the heat generation and heat transfer process of the internal components of an electric vehicle reducer,a thermal network simulation model of an electric vehicle reducer based on AMEsim software is established.It is assumed that under high lubricating conditions,the simulation of heat balance of the reducer under different condition of high-temperature and high-load different vehicle speed is completed.Then the moving particle semi-implicit method(MPS)is used to analyze the agitation flow field of the reduction gearbox at different lubricating oil quantity.Based on this,the convective heat transfer thermal resistance module of the thermal network model of the reducer is modified to obtain optimum oil quantity for reducer.The modified results indicate that under high-temperature and high-load conditions of electric vehicle reducers,a smaller amount of lubricating oil will cause the gears of reducer to be under-lubricated,resulting in higher tooth surface temperatures.Combining the thermal network model with the moving particle semi-implicit method(MPS)provides a new method for the lubrication effect analysis of electric vehicle reducers.