改进的小生境遗传算法在铁道车辆优化设计中的应用  

Improved niche genetic algorithm in optimization design of railway vehicle

作　　者：沈文林[1] 池茂儒[1] 

机构地区：[1]西南交通大学牵引动力国家重点实验室,四川成都610031

出　　处：《机械》2014年第1期5-8,31,共5页Machinery

基　　金：国家科技支撑计划(2009BAG12A02);教育部新世纪优秀人才支持计划资助项目(NCET-10-0664);教育部创新团队资助项目(IRT1178)

摘　　要：选取合适的优化方法对铁道车辆转向架悬挂参数进行优化,能有效提高车辆的动力学性能。遗传算法是一种多参数多目标优化方法,提出了采用改进的小生境遗传算法,以某铁道车辆转向架悬挂参数为设计变量,针对车辆的稳定性进行了优化设计。结果显示,通过改进的遗传算法优化出的悬挂参数能有效提高车辆的稳定性,优化后车辆的临界速度到达了600 km/h,而通过基本遗传算法和单目标优化方法得到的临界速度分别仅为500 km/h和520 km/h。研究表明,改进的小生境遗传算法能很好的实现悬挂参数间的合理匹配,优化出良好的动力学性能。A suitable optimization method can effectively improve the dynamic performance of the EMU. Genetic algorithm is a kind of multiparameter multi-objective optimization method, This paper presents an improved niche genetic algorithm to the stability of vehicle taking a railway vehicle bogie suspension parameters as design variables. The results show that the suspension parameters are optimized by the improved genetic algorithm can effectively improve the stability of the vehicle, after the optimization of the critical speed of the vehicle arrived at 600 kin/h, and by means of basic genetic algorithm, the critical speed of single objective optimization approach is only 500 km/h and 520 km/h. Research shows that the improved niche genetic algorithm can be a very good realize reasonable match between the suspension parameters, good dynamic performance optimization.

关 键 词：铁道车辆 悬挂参数 动力学性能 小生境遗传算法 

分 类 号：U270.1[机械工程—车辆工程]