基于RBPF的轨道车辆悬挂系统参数估计方法

摘要

In order to estimate the dynamic performance parameters of railway vehicle suspension system ,an RBPF (Rao Blackwellised Particle Filtering )‐based method for parameter estimation was proposed .Firstly ,the multi‐body dynamics simulation software SIMPACK was used to establish the model of the domestic rail vehi‐cle .Corresponding half‐vehicle model of lateral dynamics and state space model were established .Then ,based on the case study of the secondary lateral damper ,w hich is one of the key components of suspension system , and combined with vibration data during multi‐body dynamics simulation or the real vehicle test ,the parameters of the secondary lateral damper under normal and fault operatingconditions were estimated by applying RBPF algorithm .The estimation results showed effective and accurate estimation of the actual parameters of the key components of the suspension system with the proposed method .Through the comparison of the estimated val‐ue and the normal value ,faults can be discovered and located timely and the severity of component fault can be determined .The method of parameter estimation can provide an important theoretical basis for condition‐based repair for vehicles .%为了估计轨道车辆悬挂系统实际动力学性能参数，提出一种基于RBPF（Rao‐Blackwellised Particle Fil‐ter）的参数估计方法。应用多体动力学仿真软件SIM PACK建立国内典型轨道车辆整车模型，建立与之对应的横向动力学半车模型和状态空间模型；以悬挂系统关键部件之一的二系横向减震器为例，结合多体动力学仿真振动数据或实车试验振动数据，应用RB P F算法对二系横向减震器在正常和故障情况下实际参数值进行估计。结果表明，利用该方法可以有效准确地估计悬挂系统关键部件的实际参数值。通过比较估计值和正常值，可及时发现故障并对其进行故障定位，而且能够确定部件故障严重程度，该参数估计方法可为车辆状态修提供重要理论依据。