基于非线性动力学分析的车辆运行状态参数数据特征辨识  

Identification of data characteristics of vehicle running status parameters by nonlinear dynamic analysis

作　　者：刘兆惠 王超 吕文红 管欣[2] LIU Zhao-hui1 , WANG Chao1 , LYU Wen-hong1 , GUAN Xin2(1. College of Transportation, Shandong University of Science and Technology, Qingdao 266590, China;2. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

机构地区：[1]山东科技大学交通学院,山东青岛266590 [2]吉林大学汽车仿真与控制国家重点实验室,长春130022

出　　处：《吉林大学学报（工学版）》2018年第5期1405-1410,共6页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金重大项目(91120306/F03)

摘　　要：考虑到车辆运行状态参数时间序列不仅呈现随机性,有些还呈现混沌特性,因此,有必要对其参数数据特征进行正确辨识,以区分其参数时间序列是随机的还是混沌的。应用延迟坐标状态空间重构和最大李雅普诺夫(Lyapunov)指数法进行了非线性动力学分析,对车辆运行状态参数数据的有效信息进行深层提取。研究结果表明,由G-P算法求解得到的饱和关联维数是非整数,且最大Lyapunov指数大于零,两者综合表征此序列是混沌时间序列。因此,依据辨识结果选择适宜方法进行后继研究更具科学性。Time series of vehicle running status parameters not only present randomness,but also present chaotic characteristics.Therefore it is necessary to accurately identify the data characteristics of vehicle running status parameters,in order to identify if its parameter time series is random or chaotic.To obtain the maximum availed data information of the vehicle running status parameters.Delay-coordinate space reconstruction and the largest Lyapunov exponent method were used to carry out nonlinear dynamic analysis.Speed time series is used as an example,the results show that based on the Delay-coordinate phase space reconstruction,the saturate correlation dimension obtained by GP algorithm is not an integer,and the Max-Lyapunov exponent is grater than zero,which demonstrate speed time series is chaotic time series from two aspects.Thus,data characteristics of the vehicle running status parameters can be identified by nonlinear dynamic analysis,and then appropriate methods can be used in follow-up research based on the identification,which is more scientific.

关 键 词：交通运输系统工程 数据特征辨识 非线性动力学 车辆运行状态参数 延迟坐标状态空间重构 关联维数 最大李雅普诺夫(Lyapunov)指数 

分 类 号：U492.8[交通运输工程—交通运输规划与管理]