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Identification of Linear Tire Cornering Stiffness Using Subspace Methods

机译:使用子空间方法识别线性轮胎转弯刚度

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In this paper, subspace identification methods are proposed to estimate the linear tire cornering stiffness, which are only based on the road tests data without any prior knowledge. This kind of data-driven method has strong robustness. In order to validate the feasibility and effectiveness of the algorithms, a series of standard road tests are carried out. Comparing with different subspace algorithms used in road tests, it can be concluded that the front tire cornering stiffness can be estimated accurately by the N4SID and CCA methods when the double lane change test data are taken into analysis.
机译:在本文中,提出了子空间识别方法来估计线性轮胎转弯刚度,其仅基于道路测试数据而无需任何先验知识。这种数据驱动方法具有强大的鲁棒性。为了验证算法的可行性和有效性,进行了一系列标准的道路测试。与道路测试中使用的不同子空间算法进行比较,可以得出结论,当采用双车道改变测试数据时,通过N4SID和CCA方法可以精确地估计前轮胎转弯刚度。

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