• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2026, Vol. 62 ›› Issue (16): 95-108.doi: 10.3901/JME.260626

• 特邀专辑:轨道运载装备动态设计理论与运维技术 • 上一篇    

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考虑轨道不平顺幅值状态相关性的车辆运行平稳性随机分析

罗志翔1,2, 郭冰彬1, 赵宇2, 周生通2, 肖乾2, 周凯3, 李鸿光4,   

  1. 1. 中车株洲电力机车有限公司重载快捷大功率电力机车全国重点实验室 株洲 412001;
    2. 华东交通大学机车车辆智能运维铁路行业重点实验室 南昌 330013;
    3. 同济大学交通学院 上海 201804;
    4. 上海交通大学机械系统与振动全国重点实验室 上海 200240
  • 收稿日期:2025-08-08 修回日期:2026-02-07 发布日期:2026-10-14
  • 作者简介:罗志翔,男,1994年出生,硕士,工程师。主要研究方向为轨道车辆系统动力学与可靠性。E-mail:2330259327@qq.com;周生通(通信作者),男,1984年出生,副教授,硕士研究生导师。主要研究方向为轨道车辆系统动力学与可靠性,不确定性量化,转子动力学。E-mail:zhoust@ecjtu.edu.cn
  • 基金资助:
    国家自然科学基金(52462054,52065022)、江西省自然科学基金(20242BAB204122,20202BABL204036)和江西省教育厅科学技术研究(GJJ210638)资助项目。

Stochastic Analysis of Vehicle Ride Quality under the Correlation of Amplitude States of Track Irregularity

LUO Zhixiang1,2, GUO Bingbin1, ZHAO Yu2, ZHOU Shengtong2, XIAO Qian2, ZHOU Kai3, LI Hongguang4,   

  1. 1. The State Key Laboratory of Heavy-duty and Express High-power Electric Locomotive, CRRC Zhuzhou Locomotive Co., Ltd., Zhuzhou 412001;
    2. Key Laboratory of Railway Industry on Intelligent Operation and Maintenance for Locomotive and Vehicle, East China Jiaotong University, Nanchang 330013;
    3. College of Transportation, Tongji University, Shanghai 201804;
    4. The State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240
  • Received:2025-08-08 Revised:2026-02-07 Published:2026-10-14

摘要: 轨道不平顺幅值尺度系数(幅值系数)可用于描述轨道不平顺幅值状态的改善或劣化程度。然而,左、右钢轨的轨向和高低不平顺幅值状态往往呈现随机相关性。为此,提出一种基于典型不平顺样本和幅值系数的轨道不平顺幅值状态近似描述方法,并探讨轨向和高低幅值状态相关性对车辆运行平稳性的影响规律。首先,建立典型不平顺样本激励下的车辆动力学仿真模型;其次,将轨向、高低幅值系数视为随机变量,选用三种不同尾部属性的Copula函数描述二者的相关关系;然后,针对车辆仿真模型计算量大的问题,在有限试验设计样本下,给出基于自适应稀疏多项式混沌展开和协方差分析(Analysis of covariance,ANCOVA)灵敏度的随机分析方法和实施流程;最后,在验证模型精度的基础上,探讨不同Copula类型及相关程度下运行平稳性指标的概率分布特征和全局灵敏度规律。结果表明:① 轨向和高低幅值系数相关程度的增加会改善平均运行平稳性,但标准差增大,鲁棒性降低;② Copula类型及相关程度对平稳性指标的高阶矩(偏度、峰度)影响显著,而对低阶矩影响较小;③ 随相关性增强,三种Copula下灵敏度规律基本一致,其中高低幅值系数是运行平稳性方差的主要贡献变量,但轨向幅值系数的方差贡献随相关程度增加而上升。

关键词: 轨道不平顺, 运行平稳性, Copula函数, 多项式混沌展开, ANCOVA灵敏度

Abstract: The amplitude scale factor (short for amplitude factor) of track irregularity can be used to describe the improvement or deterioration of the amplitude state of track irregularity. However, the amplitude states of alignment and longitudinal level irregularities in the left and right rails often exhibit random correlation. To this end, an approximate description method for the amplitude state of track irregularity based on typical irregularity samples and their amplitude factors is proposed, and the influence of the correlation between alignment and longitudinal level amplitude states on vehicle ride quality is investigated. Firstly, a vehicle dynamics simulation model under the excitation of typical irregularity samples is established. Secondly, the amplitude factors of alignment and longitudinal level irregularities are taken as random variables, and three Copula functions with different tail-dependency attributes are selected to characterize the correlation between these two variables. Then, to address the high computational cost of the vehicle simulation model, a stochastic analysis method and its implementation procedure based on adaptive sparse polynomial chaos expansion(PCE) and analysis of covariance(ANCOVA) sensitivity are presented under the constraint of limited experimental design samples. Finally, on the basis of model verification, the probability distribution characteristics and global sensitivity of vehicle ride quality indices under different Copula types and different correlation degrees are discussed in detail. The results show that:① An increase in the correlation degree between alignment and longitudinal level amplitude factors leads to an improvement in the mean ride quality, but the standard deviation increases, resulting in reduced robustness;② The Copula type and correlation degree significantly affect the higher-order moments (i.e., skewness and kurtosis) of the ride quality index, while having little influence on the lower-order moments;③ As the correlation degree increases, the sensitivity patterns of the three Copula types remain generally consistent. The longitudinal level amplitude factor is the dominant contributor to the variance of ride quality, but the variance contribution of the alignment amplitude factor increases with the correlation degree.

Key words: track irregularity, ride quality, Copula function, polynomial chaos expansion, ANCOVA sensitivity

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