改进的遗传算法在同步器优化中的应用  

The Application of Improved Genetic Algorithm in Synchronizer Optimization

作　　者：童晓斌 范平清 刘天宏 李聪 TONG Xiao-bin;FAN Ping-qing;LIU Tian-hong;LI Cong(Shanghai University of Engineering Science,School of Mechanical and Automotive Engineer,Shanghai 201620,China)

机构地区：[1]上海工程技术大学机械与汽车工程学院,上海201620

出　　处：《机械设计与制造》2021年第9期190-194,共5页Machinery Design & Manufacture

基　　金：青年科学基金项目(51505275)。

摘　　要：汽车同步器是自动变速器的重要组成部分。对同步器的模拟优化能为同步器的设计生产提供重要的参考。为了获得一个较好的优化效果,提出了一种改进的遗传算法。通过对遗传算法选择过程的标准进行了改进,结合适应度函数与染色体之间差异,形成一种新的适应度函数。该函数同时考虑了选择压力和物种多样性。通过对函数中两个常量的调整,可以使算法在不同情况下可以有不同的偏重。引入两种典型测试函数的分别从高纬度变量和低纬度变量进行试验,分析改进算法中两个影响因子的作用。并与几类遗传算法进行比较,结果表明该改进的遗传算法能更快更稳定的找到较优的解。最后将改进选择策略结合自适应遗传算法对同步器进行优化,证明了该选择策略具有良好的鲁棒性和实效性。Synchronizer is an essential part of the manual transmission of automobile.The research on the optimization design of synchronizer can provide reference for the design of synchronizer.In order to achieve a better optimization effect,optimized the genetic algorithm.Proposes an improved genetic algorithm that improves the criteria for the genetic algorithm selection process.Combining the fitness function with the difference between chromosomes,a new fitness function is formed.This function takes into account both selection pressure and species diversity.By adjusting the two constants in the function,the algorithm can have different biases in different situations.Two typical test functions were introduced to test from multivariate and bivariate,and the effects of two influencing factors in the improved algorithm were analyzed.Compared with several kinds of genetic algorithms.The results show that the improved genetic algorithm can find good solutions faster and more stably.Finally,the improved selection strategy combined with adaptive genetic algorithm optimizes the synchronizer,which proves that the selection strategy has good robustness and effectiveness.

关 键 词：遗传算法 适应度函数 优化设计 汽车同步器 

分 类 号：TH16[机械工程—机械制造及自动化] TP18[自动化与计算机技术—控制理论与控制工程]