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首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part D. Journal of Automobile Engineering >Real-time estimation of tire-road friction coefficient based on lateral vehicle dynamics
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Real-time estimation of tire-road friction coefficient based on lateral vehicle dynamics

机译：基于横向车动态的轮胎道路摩擦系数的实时估计

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摘要

This study proposes a two-stage framework for real-time estimation of tire-road friction coefficient of a vehicle on the basis of lateral dynamics of the vehicle. The estimation framework employs a new cascade structure consisting of an extended Kalman filter and two unscented Kalman filters to reduce the computational burden. In the first stage, extended Kalman filter is utilized to estimate lateral velocity of the vehicle and thereby both the front and rear tires' side-slip angles. In the second stage, a two-unscented Kalman filters sub-framework is formulated in sequence to observe both the front- and rear-axle tire forces, and to subsequently identify their respective tire-road friction coefficient, regarded as two unknown states. All the measured signals required in the study could be realized from the conventional on-board sensors. Typical double-lane change and single-lane change maneuvers were designed and the developed algorithm was verified through CarSim-MATLAB/Simulink software platform considering high-, mid-, and low-friction road conditions. The simulation results show that the proposed method can yield accurate and rapid estimations of the tire-road friction coefficient for mid- and low-friction road conditions even under a single-lane change maneuver, although double-lane change maneuver is needed to accurately estimate the tire-road friction coefficient for high-friction road condition.
机译：本研究提出了基于车辆的横向动态的车辆轮胎道路摩擦系数的实时估计的两阶段框架。估计框架采用新的级联结构，包括扩展的卡尔曼滤波器和两个无名的卡尔曼滤波器，以减少计算负担。在第一阶段，扩展卡尔曼滤光器用于估计车辆的横向速度，从而均有前轮胎和后轮胎的侧滑角。在第二阶段，序列配制了一个双重卡尔曼滤波器子框架，以观察前轴胎和后轴轮胎力，并随后识别其各自的轮胎道路摩擦系数被认为是两个未知状态。可以从传统的车载传感器实现研究中所需的所有测量信号。设计了典型的双车道变化和单车道更换操作，通过Carsim-Matlab / Simulink软件平台验证了发达的算法，考虑了高，中和低摩擦的道路状况。仿真结果表明，即使在单车道变化机动下，所提出的方法也可以屈服于中低摩擦路况的轮胎道路摩擦系数的准确快速估计，尽管需要双车道变化机动来准确估计。高摩擦道路状况的轮胎道路摩擦系数。

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