基于遗传GA法的发动机悬置最优化配置的研究

Optimum Engine Mounting Layout by Genetic Algorism

在设计发动机悬置布置图时,选择左右和侧倾方式的非耦合化是非常重要的问题。可是,发动机悬置系统支承点坐标不仅有弹簧刚度,还有许多非线性参数的影响,所以,选定非线性布置图的最优值是非常困难的。为此,作为新的最优化方法引入遗传算法(以下称为G A法),进行刚度矩阵计算以及非线性参数的最优化设计,同时,运用最大概率最优化设计法(以下称为M PO D法)进行了两者精度比较的探讨,得到最优值和理论值能够很好地吻合.过去汽车专家需要2周以上的时间进行分析,现在对于经验不足的设计者运用该方法可以缩短只用1小时的时间.根据仿真确定试验结果:发动机在25H z左右加速度水平降低1/5,得到了很好的减振效果。

In the case of the engine mounting design, the decoupled layout is very important for the isolation and shock torque. On the other hand,the optimum layout is difficult to select many parameters such as mounting position, cushion rubber spring rate, etc. So, the Genetic Algorithm （ GA ） is newly applied for the stiffness matrix calculation. The Most Probable Optimal Design（ MPOD） is also tried to compare the accuracy against GA. The optimized results by GA were well matched with the theoretical calculation, which needs the special vibration analysis technique and also takes over two weeks. But, it takes only one hour, and the inexperienced engineers can easily obtain the optimized result. By the confirmation test of FEM ,the engine lateral vibration level at 25HZ dropped below 1/5 and its effects were significant.