谢斌, 罗振豪, 宋正河, 温昌凯, 张胜利, 毛恩荣. 非道路车辆轮胎-土壤相互作用建模方法及试验技术综述[J]. 农业工程学报, 2022, 38(11): 51-63. DOI: 10.11975/j.issn.1002-6819.2022.11.006
    引用本文: 谢斌, 罗振豪, 宋正河, 温昌凯, 张胜利, 毛恩荣. 非道路车辆轮胎-土壤相互作用建模方法及试验技术综述[J]. 农业工程学报, 2022, 38(11): 51-63. DOI: 10.11975/j.issn.1002-6819.2022.11.006
    Xie Bin, Luo Zhenhao, Song Zhenghe, Wen Changkai, Zhang Shengli, Mao Enrong. Review of off-road vehicle tire-soil interaction modeling methods and experimental techniques[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(11): 51-63. DOI: 10.11975/j.issn.1002-6819.2022.11.006
    Citation: Xie Bin, Luo Zhenhao, Song Zhenghe, Wen Changkai, Zhang Shengli, Mao Enrong. Review of off-road vehicle tire-soil interaction modeling methods and experimental techniques[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(11): 51-63. DOI: 10.11975/j.issn.1002-6819.2022.11.006

    非道路车辆轮胎-土壤相互作用建模方法及试验技术综述

    Review of off-road vehicle tire-soil interaction modeling methods and experimental techniques

    • 摘要: 轮胎-土壤相互作用研究是非道路车辆地面力学发展的重要基础,其中轮胎-土壤试验技术和轮胎建模方法对非道路车辆驱动系统设计、驱动算法开发以及整车牵引性能评估均具有重要意义。为明确非道路车辆轮胎-土壤相互作用研究中轮胎建模方法与试验技术的未来发展方向,该研究首先概述了国内外轮胎-土壤相互作用研究中所涉及的核心试验技术,包括土壤力学性能试验和室内单轮土槽试验,然后重点总结了轮胎-土壤相互作用的轮胎模型建立方法,将现有轮胎建模方法归纳为经验建模、数值建模和半经验建模,剖析比较了三种建模方法的优缺点和适用场景,并就每种建模方法列举了若干应用实例。最后,结合智能传感、智能测量、机器学习、整车协同等先进领域最新进展,提出了轮胎-土壤相互作用下轮胎建模方法和试验技术的未来研究重点与发展方向,以期为非道路车辆轮胎-土壤相互作用研究提供理论依据和技术参考。

       

      Abstract: A systematic review was presented for the current research progress on tire modeling and experimental techniques in the off-road vehicle tire-soil interaction. Two specific tests were involved, including the soil mechanical properties and the indoor single-wheel soil tank test. The soil mechanical properties test was divided into the soil pressure, shear strength, and soil cone index measurement. The bevameter was generally used to determine the compressive and shear strength of soils in the tire-soil interaction, which were greatly varied in the fields. Three parts were mainly divided into the bevameter, including the loading, testing, and acquisition device. The less stable and less accurate operation was found for the original bevameter that was driven by a simple hydraulic system. The servo technology and automatic control system were utilized for the higher level of intelligence so far. The soil cone index was measured by the cone index instruments. Since the measurement accuracy of the cone index meter was directly related to the smoothness of the cone penetration speed, the improved cone index meter was changed from the initial human-driven to being driven by a constant-speed hydraulic cylinder or a servo motor, particularly for the simultaneous measurement of multiple physical parameters, such as soil moisture content, in order to calibrate each other and improve the measurement accuracy. Three approaches to tire modeling were summarized in the tire-soil interaction: empirical, numerical, and semi-empirical modeling. Among them, the empirical tire-soil model was confined to a single application scenario suitable for the rapid evaluation of tire performance. The reason was that the empirical equations in the model were excessively dependent on the parameters of tires and soils, indicating the lower computational demand, but the lower model accuracy in the empirical modeling. The numerical modeling was used to accurately simulate the force characteristics of tires in different soils, but the complex structure made it difficult in the real-time simulation. Some current simplified numerical models run in real time with the ever-increasing computing power of the computer. The semi-empirical modeling integrated the tire-soil interaction and the empirical fitting, indicating an excellent balance of complexity and accuracy. The embedded platform was easily applied for the real-time model in the off-road vehicle control strategy. At the same time, several application examples of each modeling were given for comparison. In conclusion, the future directions of tire modeling and test techniques in the tire-soil interaction were proposed to combine the latest progress in advanced fields, such as intelligent sensing, intelligent measurement, machine learning, and whole-vehicle collaboration. The finding can provide a strong theoretical basis and technical reference for the off-road vehicle tire-soil interaction.

       

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