部分输入非持续激励下车辆模型系统辨识  

Vehicle Model System Identification with Non-persistent Exciting Input Partly

作　　者：袁明[1] 李松波[1] 张建武[1] 

机构地区：[1]上海交通大学机械与动力工程学院,上海200240

出　　处：《机械工程学报》2009年第9期226-232,共7页Journal of Mechanical Engineering

基　　金：上海市产学研合作资助项目

摘　　要：车速和转向盘转角是用于操纵稳定性研究的车辆模型的两个输入,但是在单次试验中两个输入难以同时作为持续激励输入,由此导致了部分输入非持续激励条件下所得到的辨识模型不完整。为了解决这一问题,通过对一组蛇行试验进行不同模型结构的系统辨识,分析以车速为非持续激励输入下车辆系统模型的结构特征,提出基于Wiener模型的非线性辨识模型结构。这一模型结构包括以转向盘转角为单输入的线性辨识模型以及以车速作为变量的非线性函数。基于子空间方法获得最低试验车速下的线性辨识模型,对不同车速下的蛇行试验数据进行相关分析,获得线性系统输出残差与车速之间的关系,使用最小二乘的方法拟合出非线性函数,从而最终形成统一的非线性辨识模型。经过实车试验验证,非线性辨识模型可以适用于不同车速下的操纵稳定性研究,其精度满足使用要求。而由于辨识建模所使用的试验均为国家标准试验,使得这一方法具有了良好的工程应用价值。Steering wheel angle and vehicle speed are two inputs of vehicle system model for handling stability research. However, the two inputs are hardly to be persistently exciting （PE） at the same time in a single test so that the identification model is incomplete under this condition. Models with varied structure are identified on the basis of a set of pylon course slalom tests in order to analyze properties of vehicle model with constant vehicle speed. According to researching findings, a nonlinear model based Wiener structure including a linear identification model with steering wheel angle as the sole input and a nonlinear function of vehicle speed is proposed. A linear model is identified by subspace method at the lowest test speed. The relationship between system output residual and vehicle speed is obtained by correlation analysis. After that, a set of nonlinear functions for every output are fitted by least square method. The final identification model containing the linear model and a nonlinear function is certified by another slalom test at different vehicle speed as a good predictor. Moreover, the tests for identification are national standard ones so this modeling method has good engineering value.

关 键 词：非线性车辆模型 非持续激励输入 子空间方法 系统辨识 

分 类 号：U461[机械工程—车辆工程]