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A cascaded scheme for high-performance estimation of vehicle states
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering ( IF 1.7 ) Pub Date : 2021-02-18 , DOI: 10.1177/0954407021993240
Jianfeng Chen 1 , Shulin Hu 1 , Yicai Ye 1 , Haoqian Huang 2 , Reza Langari 3 , Chuanye Tang 1
Affiliation  

Vehicle active safety control is bonded tightly with the accurate acquirement of vehicle states. This paper presents a cascaded scheme to realize high-performance estimation of vehicle states. To achieve the estimation with good performance, an adaptive sliding mode observer is designed for determining four longitudinal tire forces independently, and the Kalman filter is used for alleviating the inherent chattering effect. On this basis, lateral tire forces are calculated via a simplified formula based on the Dugoff tire model. Lastly, utilizing the obtained tire force information, the key states of vehicle motion are estimated through the smooth variable structure filter. Numerical experiments are conducted to testify the effectiveness of the presented estimation scheme. The results of performance comparison in different case studies show that the chattering effect can be suppressed to a great extent, and the accuracy, robustness and real-time performance to modeling uncertainty and unexpected measurements can be effectively guaranteed for vehicle state estimation by means of the proposed scheme.



中文翻译:

一种用于车辆状态的高性能估计的级联方案

车辆主动安全控制与准确获取车辆状态紧密结合。本文提出了一种级联方案来实现车辆状态的高性能估计。为了以良好的性能实现估计,设计了一个自适应滑模观察器来独立确定四个纵向轮胎力,并使用卡尔曼滤波器来减轻固有的颤振效果。在此基础上,通过基于Dugoff轮胎模型的简化公式计算轮胎横向力。最后,利用获得的轮胎力信息,通过平滑可变结构滤波器估计车辆运动的关键状态。进行了数值实验,以证明所提出的估计方案的有效性。

更新日期:2021-02-19
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