某高速汽油机主轴承润滑性能分析及优化研究

发布时间：2017-12-27 20:13

本文关键词：某高速汽油机主轴承润滑性能分析及优化研究　出处：《湖南大学》2016年硕士论文　论文类型：学位论文

【摘要】：发动机在工作过程中具有高负荷、高转速、高温等特性,这些特性直接导致了曲轴轴承系统产生振动噪音,主要零部件疲劳断裂、烧瓦以及拉缸等危害。主轴承润滑特性的好坏,不仅影响着发动机的正常工作,也影响了整机的经济性、可靠性和寿命。近年来,国内外学者一般采用多体动力学与弹性流体动力润滑耦合分析的方法来研究主轴承的润滑性能。本文采用数值仿真分析与人工智能技术相结合的方法对高速汽油机主轴承润滑性能进行分析及优化研究,论文的主要研究工作与创新点如下:(1)建立高速汽油机主轴承系统有限元模型,然后经过模态缩减,得到缩减后的有限元模型,实验结果验证了该模型的有效性。(2)建立高速汽油机曲轴轴承系统多体动力学模型,并通过台架实验,得到模型的边界条件。然后进行仿真计算,得到主轴承的最大油膜压力、最小油膜厚度、摩擦损失和机油流量等结果。通过对结果的分析可知,多个主轴承的润滑性能较差,并且由仿真计算出来的轴瓦最容易磨损的位置与主轴承实际磨损的位置一致,验证了仿真模型的正确性。由于主轴承在4000r/min工况的润滑最恶劣,后续的优化都是针对此工况进行的。(3)采用最优拉丁超设计算法对影响主轴承润滑性能的4个主要的轴瓦参数进行试验设计,然后采用径向基神经网络方法建立近似模型。以总平均摩擦损失功率最小与总平均机油流量最小作为优化的目标函数,以最小油膜厚度与最大油膜压力作为优化的边界条件,采用多岛遗传算法对近似模型进行多目标优化,在一定程度上改善了主轴承的润滑性能。
[Abstract]:The engine has a high load, high speed, high temperature and other characteristics in the work process, these characteristics led directly to the crankshaft bearing system vibration noise, fatigue fracture, the main parts of the tile burning and scuffing of cylinder bore and so harm. The good or bad lubrication characteristics of the main bearing not only affect the normal work of the engine, but also affect the economy, reliability and life of the whole machine. In recent years, scholars at home and abroad generally adopt the method of coupling analysis of multi body dynamics and elastohydrodynamic lubrication to study the lubrication performance of main bearings. In this paper by means of numerical simulation and artificial intelligence technology combined with the analysis and Optimization on the lubrication performance of high-speed gasoline engine main bearing, the main research work and innovations are as follows: (1) the establishment of high-speed gasoline engine main bearing system finite element model, and then through the finite element modal reduction, reduced model. The experimental results verify the validity of the model. (2) the multi-body dynamic model of the crankshaft bearing system of the high speed gasoline engine is set up, and the boundary conditions of the model are obtained through the bench test. The results of the maximum oil film pressure, the minimum oil film thickness, the friction loss and the oil flow rate of the main bearing are obtained by simulation. Through the analysis of the results, we can see that the lubrication performance of multiple main bearings is poor, and the location of the most easily worn wear of the main bearing is consistent with the actual wear location of the main bearing, which verifies the correctness of the simulation model. Due to the worst lubrication of the main bearing in the 4000r/min condition, the subsequent optimization is carried out by the needle. (3) using the best Latin hypergraph algorithm to design the 4 main bearing parameters that affect the lubrication performance of the main bearing, and then use the radial basis function neural network to establish the approximate model. The minimum average total friction loss power and the total average oil flow minimum as the optimization objective function, the minimum oil film thickness and maximum film pressure as the optimal boundary conditions, using the multi Island genetic algorithm for multi-objective optimization of the approximate model and improve the lubrication performance of main bearings in a certain extent.
【学位授予单位】：湖南大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TK414.11

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