基于遗传算法的LuGre轮胎模型参数辨识研究

LuGre轮胎模型是一种动态轮胎摩擦力模型,该模型能够精确描述轮胎摩擦环节的动态特性,但由其高度非线性使得参数辨识非常困难.针对LuGre轮胎模型,提出一种基于遗传算法的模型参数两步辨识方法.首先由PD控制辨识出静态参数;然后由PID控制辨识出动态参数.在每一步辨识中,均采用遗传算法作为优化工具,从而避免了采用拟和辨识方法中误差较大,试验条件难以控制的缺点.该算法仅仅使用轮胎转速数据,而转速传感器是汽车防滑刹车控制系统(ABS)的基本组成部分,因此该算法可以与ABS结合工作,低成本的实现LuGre轮胎模型参数辨识.     

基于区间灰色预测模型的飞机轮胎磨损预测技术研究

根据区间灰数的预测方法,建立了飞机轮胎磨损量的预测模型.首先分析影响轮胎磨损的因素,其次建立区间灰色预测模型,然后进行误差计算,最后得出预测结果.根据该预测模型可以得到满意的预测精度,从而为该型飞机轮胎维护制定正确的维护方案.     

饱和粘弹性土层中端承桩纵向振动的轴对称解析解

基于弹性和饱和多孔介质理论,将桩和饱和土层分别视为单相弹性介质和饱和粘弹性介质,利用Helmholtz分解和变量分离法,在频率域研究了饱和粘弹性土层中端承桩纵向振动的动力特性,给出了饱和粘弹性土层中桩纵向振动时动力响应的轴对称解析解及桩头复刚度的解析表达式．通过数值计算,给出了桩头动刚度因子和等效阻尼随激励频率的响应,考察了饱和土物性参数、桩土模量比、桩长径比、桩Poisson比等参数对桩头刚度因子和阻尼的影响．研究表明:由于考虑了桩的径向变形效应以及饱和粘弹性土层对桩的径向力作用,轴对称精确解的桩头动刚度因子和阻尼分别与经典Euler-Bernoulli杆模型桩的桩头动刚度因子和阻尼有较大的区别,特别是在若干激励频率处．因此,经典Euler-Bernoulli杆模型桩的适用性具有一定的局限,更加精确的分析应采用三维精确模型．     

统计方法在提高汽车轮胎质量研究中的应用

以乘用子午胎作为主要研究对象,根据某轮胎公司提供的数据,利用回归分析、方差分析、试验设计等统计方法,解决了在有效控制温度下,最佳肩部厚度、速度、最大负荷量,对轮胎质量的影响.     

井下钻柱纵向横向耦合振动模型建立与数值分析

针对井下钻柱运动的复杂性,基于动力学理论,建立了井下钻柱纵向和横向耦合振动的数学模型,并进行数值求解及分析.根据井下钻柱的实际工况,以整个井下钻柱为研究对象,提出了钻柱纵向和横向耦合振动的动力方程,并利用解析法和无量纲法分别求解出其动刚度和动阻尼的表达式,以及钻柱前两阶振动的固有频率.分析结果表明:当井下钻柱振动频率增大时,其动刚度呈幅值衰减的周期性变化,而其动阻尼呈幅值增强的周期性变化;井下钻柱长度和横截面面积越大,其动刚度和动阻尼的幅值越小;井下钻柱的Poisson(泊松)比对其振动的动刚度、动阻尼和前两阶固有频率没有影响;同时,井下钻柱的第二阶固有频率始终大于第一阶固有频率.该文的研究方法和模型为井下钻柱钻具分析和结果优化提供了理论参考和实际意义.     

随机激励下一类含分数阶阻尼的轮胎的振动响应

基于随机平均法研究了Kanai-Tajimi噪声激励下含分数阶阻尼的轮胎动力学系统的响应.首先将地震波近似为Kanai-Tajimi噪声,结合点接触模型和分数阶导数模型,建立轮胎的动力学方程,然后运用随机平均法求解振动位移的稳态概率密度函数的解析解,最后通过Monte-Carlo数值模拟验证了该方法的有效性.利用振动位移的概率密度求解聚丁二烯橡胶、丁基B252橡胶轮胎振动位移的均值与方差,并以此为依据考察这两类橡胶的减振性能.研究结果表明,轮胎振动位移的均值和方差随橡胶的储能模量的增大而增大,随耗散模量的增大而减小,这说明减小橡胶的储能模量或增大耗散模量可有效改善轮胎的减振性能.所得结果可为轮胎的设计与制造提供一定的理论基础.     

微加工静电超声传感器的动力学机制及其建模 *

通过对微加工静电超声传感器的动力学机制的深入研究发展了一个空气弹簧支撑的张力板模型 (tensile-plate-on-air-spring,简称为TDK模型 ) .该模型全面计及了气隙空气弹簧的刚度 ,膜片的弯曲刚度和平面张力这三个机械刚度及一个静电负刚度的影响 .根据这个模型通过适当选用传感器的几何结构 ,尺寸和材料 ,便可获得所需要的基频和带宽 ,从而为微加工超声传感器的研究和优化设计提供了一个可靠的理论基础 .     

高维纵向数据的模型平均估计

高维数据的模型选择是当今统计学研究的一个热点问题,但关于高维纵向数据方面的模型平均却少见研究,文章提出了一种利用删组交叉验证准则对高维纵向数据进行模型平均估计的方法,在最小化预测残差意义下,以删组交叉验证为准则,证明了其渐近最优性,并通过模拟研究表明,该模型平均方法在估计效果上要优于其它一些传统的模型选择和平均方法.     

有偏抽样下带信息观察和删失的面板数据的统计分析

面板数据经常出现在许多研究领域, 比如纵向跟踪研究. 在很多情况下, 纵向反应变量与观察 时间和删失时间都有关系. 本文在有偏抽样下, 针对这些相关性存在的情况, 利用一个不能观察的潜在 变量, 提出了一个联合建模方法来刻画纵向反应变量与观察时间和删失时间的相关性, 获得了模型中 回归参数的估计方程以及估计的渐近性质, 并通过数值模拟验证了这些估计在小样本下也是有效的, 同时把该估计方法用于一组实际的膀胱癌数据分析中.     

基于非约束模态的中心刚体-Timoshenko梁动力学建模与分析北大核心CSCD

梁的横向变形会导致梁纵向缩短,建模过程中考虑梁横纵变形二次耦合项则存在动力刚化现象,这说明梁的纵向变形会对模型的广义刚度造成影响.对于做旋转运动的梁结构,旋转运动时还会受到离心力的作用而产生轴向拉力,轴向拉力同样也会引起梁的轴向变形,这种影响对粗短梁更加明显.以大范围运动中心刚体-Timoshenko梁模型为研究对象:首先,运用Timoshenko梁理论以及Hamilton原理建立含离心力的动力学模型;其次,引入非约束模态概念,采用Frobenius方法求解非约束模态振型函数以及固有频率;最后,通过数值仿真探究不同恒定转速时非约束模态与约束模态广义刚度的差异和非约束模态条件下离心力对模型的影响.     

Numerical evaluation of the temperature field of steady-state rolling tires

Rubber is the main component of pneumatic tires. The tire heating is caused by the hysteresis effects due to the deformation of the rubber during operation. Tire temperatures can depend on many factors, including tire geometry, inflation pressure, vehicle load and speed, road type and temperature and environmental conditions. The focus of this study is to develop a finite element approach to computationally evaluate the temperature field of a steady-state rolling tire. For simplicity, the tire is assumed to be composed of rubber and body-ply. The nonlinear mechanical behavior of the rubber is characterized by a Mooney–Rivlin model while the body-ply is assumed to be linear elastic material. The coupled effects of the inflation pressure and vehicle loading are investigated. The influences of body-ply stiffness are studied as well. The simulation results show that loading is the main factor to determine the temperature field. The stiffer body-ply causes less deformation of rubber and consequently decreases the temperature.     

Numerical and experimental investigation on stochastic dynamic load of a heavy duty vehicle

Numerical simulation and field test are used to investigate tire dynamic load. Based on multi-body dynamics theory, a nonlinear virtual prototype model of heavy duty vehicle (DFL1250A9) is modeled. The geometric structural parameters of the vehicle system, the nonlinear characteristics of shock absorber and leaf springs are precisely described. The dynamic model is validated by testing the data, including vertical acceleration of driver seat, front wheel, intermediate wheel and rear wheel axle head. The agreement between the response of the virtual vehicle model and the measurements on the test vehicle is satisfactory. Using the reliable model, the effects of vehicle speed, load, road surface roughness and tire stiffness on tire dynamic load and dynamic load coefficient (DLC) are discussed. The results demonstrate that the proposed model can offer efficient and realistic simulation for stochastic dynamic loads, so as to investigate vehicle road-friendliness.     

Estimation of dry road braking distance considering frictional energy of patterned tires

This paper is concerned with the braking distance estimation of tire controlled by anti-lock brake system (ABS) according to a numerical–analytical method. While the frictional heat dissipation at disc pad is derived analytically, the tire frictional energy loss is computed by the 3D dynamic rolling analysis of patterned tire. Since the tire rolling analysis to obtain the time history of the frictional energy rate for the entire braking period is impractical, we alternatively seek the tire frictional energy rate curve versus the lapse of time by interpolating the discretized frictional energy rates computed at intervals of 10 km/h. The effect of ABS is numerically implemented by specifying the corresponding tire angular velocity to the dynamic rolling analysis. Applying the energy conservation law to each speed interval determines the interval-wise braking times and distances from which the total braking time and distance are predicted. Illustrative numerical experiment is presented together with the comparison with the experimental estimation.     

纵向数据下广义估计方程估计

广义估计方程方法是一种最一般的参数估计方法,广泛地应用于生物统计、经济计量、医疗保险等领域.在纵向数据下,由于组间数据是相关的,为了提高估计的效率,广义估计方程方法一般需要考虑个体组内相关性.因此,大多数文献对个体组内的协方差矩阵进行参数假设,但假设的合理性及协方差矩阵估计的好坏对参数估计效率产生很大影响,同时参数假设也可能导致模型误判.针对纵向数据下广义估计方程,本文提出了改进的GMM方法和经验似然方法,并对给出的估计量建立了大样本性质.其中分块的思想,避免了对个体组内相关性结构进行假设,从这种意义上说,这种方法具有一定的稳健性.我们还通过两个模拟的例子,考察了文中提出估计量的有限样本性质.     

Variable selection in the partially linear errors-in-variables models for longitudinal data

This paper proposes a new approach for variable selection in partially linear errors-in-variables (EV) models for longitudinal data by penalizing appropriate estimating functions. We apply the SCAD penalty to simultaneously select significant variables and estimate unknown parameters. The rate of convergence and the asymptotic normality of the resulting estimators are established. Furthermore, with proper choice of regularization parameters, we show that the proposed estimators perform as well as the oracle procedure. A new algorithm is proposed for solving penalized estimating equation. The asymptotic results are augmented by a simulation study.     

Weighted estimating equation: modified GEE in longitudinal data analysis

The method of generalized estimating equations （GEE） introduced by K. Y. Liang and S. L. Zeger has been widely used to analyze longitudinal data. Recently, this method has been criticized for a failure to protect against misspecification of working correlation models, which in some cases leads to loss of efficiency or infeasibility of solutions. In this paper, we present a new method named as ＇weighted estimating equations （WEE）＇ for estimating the correlation parameters. The new estimates of correlation parameters are obtained as the solutions of these weighted estimating equations. For some commonly assumed correlation structures, we show that there exists a unique feasible solution to these weighted estimating equations regardless the correlation structure is correctly specified or not. The new feasible estimates of correlation parameters are consistent when the working correlation structure is correctly specified. Simulation results suggest that the new method works well in finite samples.     

Semiparametric analysis of longitudinal data with informative observation times

In many longitudinal studies,observation times as well as censoring times may be correlated with longitudinal responses.This paper considers a multiplicative random effects model for the longitudinal response where these correlations may exist and a joint modeling approach is proposed via a shared latent variable.For inference about regression parameters,estimating equation approaches are developed and asymptotic properties of the proposed estimators are established.The finite sample behavior of the methods is examined through simulation studies and an application to a data set from a bladder cancer study is provided for illustration.