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基于多运动场耦合的转向系统多目标优化设计
引用本文:石博强,唐歌腾,余国卿,张文明.基于多运动场耦合的转向系统多目标优化设计[J].北京理工大学学报,2015,35(6):580-584.
作者姓名:石博强  唐歌腾  余国卿  张文明
作者单位:北京科技大学机械工程学院,北京,100083;交通运输部公路科学研究院运输车辆运行安全技术交通行业重点实验室,北京,100088
基金项目:国家自然科学基金资助项目(51075029);北京市自然科学基金资助项目(3093022)
摘    要:考虑悬挂缸的动刚度特性及轮胎的非线性特性,将转向机构、悬挂、轮胎三运动场进行耦合处理,建立转向系统多目标优化数学模型,对400 t重型矿用自卸车转向系统进行更精确地优化设计. 应用物理规划法,构建转向系统物理规划优化设计模型,通过遗传算法进行模型求解及初步筛选,最后对车辆进行紧急双移线试验,仿真分析其操纵稳定性,实现转向系统优化解集合的最终筛选,为最优解的确定提供了一种新方法. 

关 键 词:多运动场耦合  多目标优化  物理规划  遗传算法  操纵稳定性
收稿时间:2014/6/11 0:00:00

Multi-Objective Optimization Design on Steering System Based on Multi-Motion-Field Coupling
SHI Bo-qiang,TANG Ge-teng,YU Guo-qing and ZHANG Wen-ming.Multi-Objective Optimization Design on Steering System Based on Multi-Motion-Field Coupling[J].Journal of Beijing Institute of Technology(Natural Science Edition),2015,35(6):580-584.
Authors:SHI Bo-qiang  TANG Ge-teng  YU Guo-qing and ZHANG Wen-ming
Institution:1.College of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China2.Key Laboratory of Operation Safety Technology on Transport Vehicles Ministry of Communication, Research Institute of Highway Ministry of Transport, Beijing 100088, China
Abstract:In order to gain more precise optimization design of the 400 t heavy-duty mining dump truck's steering system, meanwhile considering dynamic stiffness characteristic of suspension cylinder and nonlinear characteristic of tire, this paper coupled steering mechanism, suspension and tire these three motion fields, then established the mathematical model of steering system for multi-objective optimization. With the use of physical programming method, the physical programming optimal design model of steering system was established, and the optimal solution and preliminary screening were achieved with genetic algorithm. At last, the Trucksim were used to handle stability simulations, which is the emergency double-lane change test. It ultimately selected the optimal solution for design of steering system, and provided a new method for determining the optimal solution.
Keywords:multi-motion-field coupling  multi-objective optimization  physical programming  genetic algorithm  handling stability
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