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Vehicle tyre/road interaction modeling and identification of its parameters using real-time trust-region methods

机译:使用实时信任区域方法的车辆轮胎/道路交互建模和识别其参数

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Driving safety can be achieved by better understanding critical situations which may require the knowledge of interaction between vehicle tyres and the road surfaces. It is thus essential to have a good estimation of the tyre/road friction parameters in real-time. The paper deals with the trust-region based method for on-line estimation of tyre/road friction parameters. This method provides an appropriate modeling (of a vehicle and the tyre/road contact) to observe the tyre/road friction coefficients directly using measurable signals in real-time. In this work, we present a new LuGre model-based nonlinear least squares (NLLS) parameter estimation algorithm using vehicle dynamic to obtain the parameters of LuGre model based on recursive nonlinear optimization of the curve fitting errors. The proposed estimation method can also be utilized in large-scale problems with similar conditions. Very promising results have been obtained in real-time simulations for most of the driving and road situations.
机译:通过更好地理解可能需要车辆轮胎与道路表面之间的相互作用的关键情况,可以实现驾驶安全性。因此,必须实时地估计轮胎/道路摩擦参数。本文涉及基于信任区域的轮胎/道路摩擦参数的在线估计方法。该方法提供适当的建模(车辆和轮胎/道路接触),以实时地使用可测量的信号直接观察轮胎/道路摩擦系数。在这项工作中,我们介绍了一种新的基于Lugre模型的非线性最小二乘法(NLLS)参数估计算法,使用车辆动态来获得基于曲线拟合误差的递归非线性优化的Lugre模型的参数。所提出的估计方法也可以在具有类似条件的大规模问题中使用。对于大多数驾驶和道路状况的实时模拟,已经获得了非常有前途的结果。

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