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Study on the Lateral Stability of B-Double Based on Clustering Analysis

机译:基于聚类分析的B-Double横向稳定性研究

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A novel method is proposed to establish the stability criterion of B-double based on the clustering algorithm. The patterns recognizing in the lateral stability of B-double is studied. The vehicle model of multi-degree of freedom is established in the TruckSim. The off-line clustering center is obtained by K-means clustering. The TruckSim & Simulink co-simulation platform is built to identify the vehicle driving stability according to the online identification. The method is of data mining, which makes full use of the comparison of offline data and real-time data. The simulation results show that the method can accurately and real-time quantify the lateral driving stability of the B-double considering various factors, which can provide the criterion for intervention timing and degree of control system.
机译:提出了一种基于聚类算法的B双级的稳定性标准建立一种新的方法。研究了B-Double的横向稳定性的图案。在卡车里建立了多维自由度的车辆模型。通过k-means聚类获得离线聚类中心。建立了TruckSIM和Simulink共模平台以根据在线识别识别车辆驾驶稳定性。该方法是数据挖掘,可以充分利用离线数据和实时数据的比较。仿真结果表明,考虑各种因素,该方法可以准确地实时量化B双倍的横向驱动稳定性,这可以提供用于介入时序和控制系统程度的标准。

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