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随机结构参数车辆在随机激励下的振动响应
引用本文:贾爱芹,陈建军,曹鸿钧.随机结构参数车辆在随机激励下的振动响应[J].西南交通大学学报,2014,27(3):438-443.
作者姓名:贾爱芹  陈建军  曹鸿钧
基金项目:国家863计划资助项目(2006AA04Z402)中央高校基本科研业务费专项资金资助项目(JY10000904012)
摘    要:为分析随机结构参数对车辆系统随机振动响应的影响,通过1/4车辆模型,研究了具有随机结构参数的非线性车辆系统在随机过程激励下的振动响应.将簧上质量、簧下质量、悬挂阻尼、悬挂刚度以及轮胎刚度均视为随机变量,考虑轮胎与车身之间弹簧的非线性,将路面不平整引起的对车辆的激励作为平稳白噪声过程建立系统的动力性方程,采用能量差法对非线性车辆系统进行等效线性化处理;通过求解李雅普诺夫方程,获得平稳随机振动响应协方差矩阵,并通过多次迭代求得稳定的等效线性车辆系统参数.算例计算结果表明:能量差法计算位移的相对误差为6.841 5%,而方程差法的相对误差为8.150 5%;用此方法计算随机响应的方差值仅用了0.8 s,而用Monte Carlo法模拟1 000次耗时70 min. 

关 键 词:非线性车辆系统    等效线性化    能量差    随机参数    随机响应
收稿时间:2012-12-10

Vibration Response of Vehicle with Stochastic Structural Parameters under Random Excitation
JIA Aiqin,CHEN Jianjun,CAO Hongjun.Vibration Response of Vehicle with Stochastic Structural Parameters under Random Excitation[J].Journal of Southwest Jiaotong University,2014,27(3):438-443.
Authors:JIA Aiqin  CHEN Jianjun  CAO Hongjun
Abstract:To investigate the influence of random structure parameters on vehicle vibration responses, the random vibration responses of a vehicle system with uncertain parameters under random road excitations were investigated using a quarter-vehicle model. A dynamic model for the system was established. In this model, sprung mass, unsprung mass, suspension damping, suspension and tyre stiffness are considered as random variables, springs between tires and vehicle body are thought to be nonlinear, and road irregularity is considered to be a white noise process. The nonlinear vehicle system was linearized by the energy difference method, a stationary covariance matrix for the random vibration responses was obtained by solving the Lyapunov equations, and the stable equivalent linear system parameters of vehicle were gained through iterations. The example calculation results show that this method can improve the accuracy and efficiency of computation—the relative error of displacement is 6.841 5% to the energy difference method, while it is 8.150 5% to the equation difference method; solving the variance value of random responses using the energy difference method uses only 0.8 s, and while simulating 1 000 times using the Monte Carlo method 70 min. 
Keywords:
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