铁道车辆悬挂系统振动特征频率灵敏度分析

摘 要: 针对二阶常微分方程描述的车辆系统动力学数学模型,推导了系统特征参数灵敏度分析表达式。以二系悬挂6自由度铁道车辆悬挂系统为例进行了车辆系统振动特性参数灵敏度分析,讨论了车辆系统刚度矩阵中对车辆沉浮和点头振动影响较大的元素,通过灵敏度分析指明了悬挂参数的修改方向,为车辆悬挂系统的动态设计提供了有效的方法。
     

Identification of composite uncertain material parameters from experimental modal data

Stochastic analysis of structures using probability methods requires the statistical knowledge of uncertain material parameters. This is often quite easier to identify these statistics indirectly from structure response by solving an inverse stochastic problem. In this paper, a robust and efficient inverse stochastic method based on the non-sampling generalized polynomial chaos method is presented for identifying uncertain elastic parameters from experimental modal data. A data set on natural frequencies is collected from experimental modal analysis for sample orthotropic plates. The Pearson model is used to identify the distribution functions of the measured natural frequencies. This realization is then employed to construct the random orthogonal basis for each vibration mode. The uncertain parameters are represented by polynomial chaos expansions with unknown coefficients and the same random orthogonal basis as the vibration modes. The coefficients are identified via a stochastic inverse problem. The results show good agreement with experimental data.     

基于多体力学的汽车空气弹簧悬架优化

基于ADAMS/View软件对湖南大学自主研发的某一车型,以提高整车行驶平顺性为目的,综合考虑阻尼系数、悬架刚度和非簧载质量各因素对平顺性的影响,建立了空气弹簧悬架及整车仿真分析模型,构造了仿真分析所需路谱的高程样本,对其影响汽车安全性、平稳性、舒适性的参数进行敏感性分析,并在此基础上对空气弹簧悬架系统参数进行优化设计.通过实车道路试验和仿真结果的对比,验证了仿真的可信度及可行性.     

Non-stationary random response analysis of structures with uncertain parameters

This paper proposes a non-stationary random response analysis method of structures with uncertain parameters. The structural physical parameters and the input parameters are considered as random variables or interval variables. By using the pseudo-excitation method and the direct differentiation method (DDM), the analytical expression of the time-varying power spectrum and the time-varying variance of the structure response can be obtained in the framework of first order perturbation approaches. In addition, the analytical expression of the first-order and second-order partial derivative (e.g., time-varying sensitivity coefficient) for the time-varying power spectrum and the time-varying variance of the structure response expressed via the uncertainty parameters can also be determined. Based on this and the perturbation technique, the probabilistic and non-probabilistic analysis methods to calculate the upper and lower bounds of the time-varying variance of the structure response are proposed. Finally the effectiveness of the proposed method is demonstrated by numerical examples compared with the Monte Carlo solutions and the vertex solutions.     

Multi-objective optimization of suspension parameters for rail vehicles based on a virtual prototype surrogate model

This research is intended to develop a suspension parameter optimization approach based on a virtual prototype surrogate model of rail vehicles considering the coupling effects of suspension parameters. In order to analyze the effects on the dynamic indexes, which were affected by the suspension parameters, a virtual prototype model of a rail vehicle was established. The indexes of lateral ride quality and motion stability were obtained under different combinations of suspension parameters by design of experiment and simulation of virtual prototype. For constructing objective function of multi-objective optimization model for suspension parameters, the suspension parameters that have significant effects on ride quality and motion stability simultaneously were taken as the design variables, and thereafter Kriging models of lateral ride quality index, derailment coefficient, and reduction ratio of wheel load were obtained. On this basis, the multi-objective optimization model of suspension parameters was established, in which the objective function was combined with the three Kriging models. Then, the Pareto optimal solution set and concrete value of suspension parameters were sought using the NSGA-II algorithm. The dynamic simulation results indicated that both ride quality and motion stability of the rail vehicle had been improved after the multi-objective optimization of suspension parameters.     

基于惯容器-弹簧结构体系的车辆悬架结构设计与试验

为进一步拓宽应用惯容器的车辆悬架结构设计思路,基于"惯容器-弹簧-质量"系统反共振,以并联的"惯容器-弹簧"二元件为结构基础构建两种不同车辆ISD悬架结构。通过遗传优化算法获得悬架结构参数,在频域范围内对比分析传统被动悬架及Ⅰ、Ⅱ型悬架系统性能。结果表明,所建悬架结构可有效抑制车身偏频处振动。对性能较优Ⅱ型悬架进行试验研究,搭建含Ⅱ型悬架结构的车辆四分之一悬架试验台架,在随机路面输入下对悬架平顺性评价指标定量分析。悬架动行程均方根值提升16.24%,轮胎动载荷均方根值提升6.75%,车身加速度均方根值略有改善。表明该悬架结构能有效改善车辆的行驶平顺性与操纵稳定性。     

基于模糊控制的商用车驾驶室悬置有限带宽主动控制系统研究简

 建立了含驾驶室的商用车十自由度整车数学模型,对安装了驾驶室有限带宽主动悬置的商用车进行模糊控制系统设计,该控制系统全面考虑了驾驶室质心处垂直、俯仰、侧倾方向振动,并采用遗传算法对模糊控制器增益因子进行优化．以积分白噪声随机路面输入作为激励进行振动仿真,仿真结果表明采用本文设计的驾驶室有限带宽主动悬置模糊控制系统相对全浮式悬置系统有效降低了驾驶室质心垂直、俯仰和侧倾加速度,一定程度上提高了商用车行驶平顺性和乘坐舒适性．     

八轴连通式油气悬架车辆行驶性能和通过性能研究

行驶性能和通过性能是评估车辆越野性能的基本指标.为得到八轴连通式油气悬架车辆的越野性能,分别对行驶性能和通过性能开展了研究.简化了整车的物理模型,根据拉格朗日方程推导了车辆的振动方程,建立了白噪声路面输入方程;通过仿真结果与实验结果的对比,验证了柔性模型的合理性.基于柔性模型,以路面不平度系数为输入变量,得到了车辆在较...     

Probability density evolution method for dynamic response analysis of structures with uncertain parameters

Probability density evolution method is proposed for dynamic response analysis of structures with random parameters. In the present paper, a probability density evolution equation (PDEE) is derived according to the principle of preservation of probability. With the state equation expression, the PDEE is further reduced to a one-dimensional partial differential equation. The numerical algorithm is studied through combining the precise time integration method and the finite difference method with TVD schemes. The proposed method can provide the probability density function (PDF) and its evolution, rather than the second-order statistical quantities, of the stochastic responses. Numerical examples, including a SDOF system and an 8-story frame, are investigated. The results demonstrate that the proposed method is of high accuracy and efficiency. Some characteristics of the PDF and its evolution of the stochastic responses are observed. The PDFs evidence heavy variance against time. Usually, they are much irregular and far from well-known regular distribution types. Additionally, the coefficients of variation of the random parameters have significant influence on PDF and second-order statistical quantities of responses of the stochastic structure.The support of the Natural Science Funds for Distinguished Young Scholars of China (Grant No.59825105) and the Natural Science Funds for Innovative Research Groups of China (Grant No.50321803) are gratefully appreciated.     

Investigating variability of fatigue indicator parameters of two-phase nickel-based superalloy microstructures

Variability of fatigue properties of Nickel-based superalloys induced by microstructure feature uncertainties is investigated. The microstructure at one material point is described by its grain size and orientation features, as well as the volume fraction of the γ′ phase. Principal component analysis (PCA) is introduced to reduce the dimensionality of the microstructure feature space. PCA and kernel PCA (KPCA) techniques are presented and compared. Reduced representations of input features are mapped to uniform or standard Gaussian distributions through polynomial chaos expansion (PCE) so that the sampling of new microstructure realizations becomes feasible. A crystal plasticity constitutive model is adopted to evaluate fatigue properties of two-phase superalloy microstructures under cyclic loading. The fatigue properties are measured by strain-based fatigue indicator parameters (FIP). Adaptive sparse grid collocation (ASGC) and Monte Carlo (MC) methods are used to establish the relation between microstructure feature uncertainties and the variability of macroscopic properties. Convergence with increasing dimensionality of the reduced surrogate stochastic space is studied. Distributions of FIPs and the convex hulls describing the envelope of these parameters in the presence of microstructure uncertainties are shown.     

Galerkin based generalized ANOVA for the solution of stochastic steady state diffusion problems

This work presents a novel approach, referred here as Galerkin based generalized analysis of variance decomposition (GG-ANOVA), for the solution of stochastic steady state diffusion problems. The proposed approach utilizes generalized ANOVA (G-ANOVA) expansion to represent the unknown stochastic response and Galerkin projection to decompose the stochastic differential equation into a set of coupled differential equations. The coupled set of partial differential equations obtained are solved using finite difference method and homotopy algorithm. Implementation of the proposed approach for solving stochastic steady state diffusion problems has been illustrated with three numerical examples. For all the examples, results obtained are in excellent agreement with the benchmark solutions. Additionally, for the second and third problems, results obtained have also been compared with those obtained using polynomial chaos expansion (PCE) and conventional G-ANOVA. It is observed that the proposed approach yields highly accurate result outperforming both PCE and G-ANOVA. Moreover, computational time required using GG-ANOVA is in close proximity of G-ANOVA and less as compared to PCE.     

Sparse polynomial chaos expansions of frequency response functions using stochastic frequency transformation

Frequency response functions (FRFs) are important for assessing the behavior of stochastic linear dynamic systems. For large systems, their evaluations are time-consuming even for a single simulation. In such cases, uncertainty quantification by crude Monte-Carlo simulation is not feasible. In this paper, we propose the use of sparse adaptive polynomial chaos expansions (PCE) as a surrogate of the full model. To overcome known limitations of PCE when applied to FRF simulation, we propose a frequency transformation strategy that maximizes the similarity between FRFs prior to the calculation of the PCE surrogate. This strategy results in lower-order PCEs for each frequency. Principal component analysis is then employed to reduce the number of random outputs. The proposed approach is applied to two case studies: a simple 2-DOF system and a 6-DOF system with 16 random inputs. The accuracy assessment of the results indicates that the proposed approach can predict single FRFs accurately. Besides, it is shown that the first two moments of the FRFs obtained by the PCE converge to the reference results faster than with the Monte-Carlo (MC) methods.     

Stochastic dynamic analysis of a functionally graded thick hollow cylinder with uncertain material properties subjected to shock loading

This paper presents an investigation of the stochastic dynamic response of a functionally graded (FG) thick hollow cylinder with uncertain material properties subjected to mechanical shock loading. The mechanical properties are considered to vary across thickness of FG cylinder as a non-linear power function of radius. To obtain the radial displacement in each point, the Navier equation in displacement form is derived using linear functionally graded elements. The Galerkin finite element and Newmark finite difference methods along with the Monte Carlo simulation are employed to deal with the statistical response of the FG cylinder. The mean and variance of radial displacements are calculated in various points across thickness for different values of volume fraction exponents. The results are used to quantify the effects of variations in the mechanical properties on the dynamic response and safety within the FG cylinder.     

On the accuracy of the polynomial chaos approximation

Polynomial chaos representations for non-Gaussian random variables and stochastic processes are infinite series of Hermite polynomials of standard Gaussian random variables with deterministic coefficients. Finite truncations of these series are referred to as polynomial chaos (PC) approximations. This paper explores features and limitations of PC approximations. Metrics are developed to assess the accuracy of the PC approximation. A collection of simple, but relevant examples is examined in this paper. The number of terms in the PC approximations used in the examples exceeds the number of terms retained in most current applications. For the examples considered, it is demonstrated that (1) the accuracy of the PC approximation improves in some metrics as additional terms are retained, but does not exhibit this behavior in all metrics considered in the paper, (2) PC approximations for strictly stationary, non-Gaussian stochastic processes are initially nonstationary and gradually may approach weak stationarity as the number of terms retained increases, and (3) the development of PC approximations for certain processes may become computationally demanding, or even prohibitive, because of the large number of coefficients that need to be calculated. However, there have been many applications in which PC approximations have been successful.     

轮轨磨耗状态下悬挂参数失效对车辆动力学性能影响

为了研究悬挂参数失效对车辆系统动力学性能的影响,建立高速车辆系统动力学模型和悬挂参数失效模型,针对新轮轨、磨耗后轮轨进行轮轨接触几何关系和动力学仿真计算,分析当悬挂参数正常工作和失效时,车辆动力学性能的变化。结果表明：与新轮轨相比,轮轨磨耗状态下的等效锥度、滚动圆半径差和左右轮轨接触角度差变大;轮轨磨耗造成蛇行失稳临界速度下降,运行平稳性和曲线通过能力变差;悬挂系统失效方式不同,对车辆系统动力学的性能和车体的动态响应影响程度不同;车辆的悬挂参数优化应考虑轮轨磨耗的影响。     

基于AHP的车辆主动悬架LQG控制器设计

基于层次分析法（AHP）设计了一种能够降低车身加速度（BA）、悬架动行程（SWS）和轮胎动位移（DTD）的车辆主动悬架线性最优（LQG）控制器。首先建立了2自由度1/4车辆主被动悬架动力学模型;然后采用AHP确定了悬架各性能评价指标的加权系数并利用最优控制理论设计了车辆主动悬架控制器;最后在Matlab/Simulink环境下进行了仿真分析。对仿真结果进行对比后表明：在特定工况下通过对加权系数的合理选取,BA、SWS和DTD比被动悬架分别减小了18.73%、22.22%和4.76%,且主动控制力的均方根值为535.3994N。     

车辆传动系统线性弯扭耦合振动响应灵敏度研究

由于车辆上采用的发动机工作转速较宽,无法完全避免共振现象的发生。针对上述问题对车辆传动系统动态特性的分析从固有特性的分析转移到动力响应的分析上来,并衍生出基于动力响应的灵敏度分析。以某车辆传动系统作为研究对象,建立了线性弯扭耦合集中参数动力学模型及方程。应用直接求导法建立了灵敏度方程,进行了响应灵敏度计算,分别研究设计参数对扭转方向的力矩和弯曲方向上力的影响,获得了轴段附加扭转力矩和轴承支反力对设计参数的灵敏度,并将同一灵敏度量在纯扭和弯扭系统下的结果进行对比。研究表明:弯扭模型计算出的响应灵敏度值比纯扭模型的计算结果小10%~20%,但规律趋于一致;弯曲方向上的力和扭转方向上的力矩对设计参数的灵敏度与该位置的振动能量大小相关,能量越大其对同一参数的灵敏度也越大。     

基于UG/Motion重型货车主副弹簧悬架动力学仿真分析系统的构建

摘　要：提出了一种基于UG/Motion构建重型货车主副弹簧悬架动力学仿真分析系统的新方法,并应用该方法开发出了相应的软件原型系统。基于两自由度1/4车辆虚拟样机模型,原型系统的仿真分析模块可方便、快捷的实现虚拟样机模型主要设计参数的修改及基于谐波叠加法各种标准等级时域路面不平度的模拟生成。仿真分析模块通过调用UG/Motion集成的RecurDyn解算器来获取仿真分析结果,通过集成Matlab的绘图功能对分析结果进行输出查看;系统的遗传优化设计模块以整个载荷范围内悬挂质量加速度均方根值最小为目标函数,可对悬架的阻尼系数、主副弹簧刚度比和临界载荷比进行了动力学优化。通过一个设计实例验证了原型系统构建的正确性及遗传优化设计模块的有效性。     

油气主动悬架不确定性对重载车辆平顺性的影响分析

重载车辆主动悬架由于受到系统内部不确定和外部扰动的共同作用，使得闭环系统鲁棒性以及由此引出的车辆行驶平顺性变化需要引起特别的重视。本文利用线性分式变换理论对车辆主动悬架系统进行了不确定建模分析，应用鲁棒控制和结构奇异值理论，设计了鲁棒控制器。讨论了在车辆系统参数变化和存在输入端未建模动态不确定的条件下，不确定对车辆平顺性的影响。研究结果表明，在不确定范围内，鲁棒控制器不但保证了主动悬架系统平顺性的名义性能，而且，主动悬架系统各项平顺性能指标的鲁棒性同样得到了满足。     

Effect of oxy-hydrogen blending with gasoline on vehicle performance parameters and optimization using response surface methodology

ABSTRACT

Rapid decline in fossil fuel reservoirs has attracted researchers to use a variety of fuel blends in Spark ignition (SI) and Compression ignition (CI) engines demonstrating similar performance and lower emissions. Oxy-hydrogen gas obtained through electrolysis has been successfully tested for this use. This paper presents a two wheeler chassis dynamometer based study of a two wheeler loaded with newly developed single cylinder variable compression ratio (VCR) engine utilizing different blends of gasoline and oxy-hydrogen gas. Variation in fuel average performance (FAP), wheel power (WP) and acceleration performance (AP) due to oxy-hydrogen blending with gasoline is studied and compared with neat gasoline at five different gears. Further multi objective optimization of FAP and WP is carried out using response surface methodology (RSM). Regression models are postulated for predicting FAP and WP at different levels of compression ratio (CR) and oxy-hydrogen gasoline blends. Interaction between CR and oxy-hydrogen-gasoline blending is also studied and discussed. Modification carried out on an engine improves vehicle performance parameters and oxy-hydrogen gasoline blending further enhances the improvements. Maximum FAP and WP in top gear is obtained at highest CR of 11.57:1 and a oxy-hydrogen gasoline blend with 112.558 ml/min flow rate of oxy-hydrogen gas.