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某大型运输车的时域平顺性仿真分析
引用本文:荣吉利,郑育龙,刘琥,何丽,王玺.某大型运输车的时域平顺性仿真分析[J].北京理工大学学报,2017,37(2):146-150,156.
作者姓名:荣吉利  郑育龙  刘琥  何丽  王玺
作者单位:北京理工大学宇航学院,北京,100081;北京航天发射技术研究所,北京,100076
基金项目:北京航天发射技术研究所创新课题基金资助项目(yy_scx)
摘    要:为解决某大型运输车在运输过程中,车载精密仪器振动过大而影响其使用性能的问题,基于拉格朗日原理,建立了某大型运输车仪器-车-路耦合的19自由度振动动力学模型;利用白噪声模块,构建了随机路面激励时域模型;采用时域分析方法,分析了路面不平度、车速以及仪器悬置刚度阻尼对仪器振动加速度影响.并采用粒子群算法,对相关参数进行优化.研究表明:通过提高路面等级、选择适当的行车速度、适当的降低仪器悬置的刚度和阻尼,能够有效降低仪器的振动加速度,提高大型运输车的平顺性. 

关 键 词:仪器-车-路耦合  路面不平度时域模型  振动加速度  粒子群算法  平顺性
收稿时间:2015/7/10 0:00:00

Time Domain Method in Large Freight Vehicle Ride Comfort Analysis
RONG Ji-li,ZHENG Yu-long,LIU Hu,HE Li and WANG Xi.Time Domain Method in Large Freight Vehicle Ride Comfort Analysis[J].Journal of Beijing Institute of Technology(Natural Science Edition),2017,37(2):146-150,156.
Authors:RONG Ji-li  ZHENG Yu-long  LIU Hu  HE Li and WANG Xi
Institution:1. School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China;2. Beijing Institute of Space Launch Technology, Beijing 100076, China
Abstract:In order to solve the problem that vibration of vehicle-mount facility is too large to keep its performance in the running large freight vehicle, a facility-vehicle-road coupled model with 19 degrees of freedom was built based on Lagrange''s principle. A time domain incentive model of random road was constructed by using a white noise-based model. And based on above two models, vibration of the facility on the vehicle was studied in different situations by time domain analysis method. And particle swarm optimization (PSO) was used to optimize related parameters. Results indicate that improving road level, choosing an appropriate speed, appropriately reducing the stiffness and damping of the facility''s suspension can reduce the vibration of the facility and improve the large freight vehicle ride comfort. The research results provide a certain reference value to engineering problems.
Keywords:facility-vehicle-road coupling  time domain incentive model of random road  vibration acceleration  PSO  riding comfort
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