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首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers. Part K, Journal of Multi-body Dynamics >The lubrication analysis of the piston skirt-liner system based on design of experiment and particle swarm optimization-support vector regression
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The lubrication analysis of the piston skirt-liner system based on design of experiment and particle swarm optimization-support vector regression

机译：基于实验设计和粒子群优化-支持向量回归的活塞裙衬系统润滑分析

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摘要

Good design for the piston skirt can improve efficiency without harming emissions, while it simultaneously reduces wear and improves the reliability of the engine. In this paper, the finite element method is applied to solve the Reynolds equation to analyze the piston skirt-liner system lubrication, and the side motion of piston skirt solved with Runge-Kutta is coupled with lubrication. Some factors that have an effect on the lubrication and dynamic characteristics are selected as variables, such as the clearance, offset distance of the piston pin, bump position, curvature, the length of piston skirt, and the ellipticity of the piston skirt. The orthogonal experimental design which includes six factors with five levels is used to analyze the dominance of these structure factors, and the effects of all the responses for the structural parameters to the friction loss are also identified, and the orthogonal samples simulated by the experiment are conducted to do the regression for the piston skirt. Some regression models are introduced to predict the friction loss, the precise comparison of all the models are compared, and the larger error appears in these prediction models, and then the particle swarm optimization-support vector regression is also used to predict the friction loss, and the results agree well with each other. All the analyses are very useful to provide guidance for the design of the piston skirt-liner during the development of the engine.
机译：活塞裙的良好设计可以在不损害排放的情况下提高效率，同时减少磨损并提高发动机的可靠性。本文采用有限元方法对雷诺方程进行求解，以分析活塞裙-缸套-系统的润滑，并通过Runge-Kutta解决了活塞裙的侧向运动与润滑的关系。选择一些会影响润滑和动态特性的因素作为变量，例如间隙，活塞销的偏移距离，碰撞位置，曲率，活塞裙的长度和活塞裙的椭圆度。采用包含五个级别的六个因子的正交实验设计来分析这些结构因子的优势，并确定结构参数的所有响应对摩擦损失的影响，并通过实验模拟正交样本进行活塞裙的回归分析。引入了一些回归模型来预测摩擦损失，比较所有模型的精确比较，并在这些预测模型中出现较大的误差，然后还使用粒子群优化-支持向量回归来预测摩擦损失，结果彼此吻合。所有这些分析对于在发动机开发过程中为活塞裙衬套的设计提供指导都是非常有用的。

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