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An Intelligent Tire Based Tire-Road Friction Estimation Technique and Adaptive Wheel Slip Controller for Antilock Brake System

机译:基于智能轮胎的轮胎-道路摩擦估计技术和自适应轮滑控制器用于防抱死制动系统

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摘要

The contact between the tire and the road is the key enabler of vehicle acceleration, deceleration and steering. However, due to changes to the road conditions, the driver's ability to maintain a stable vehicle may be at risk. In many cases, this requires intervention from the chassis control systems onboard the vehicle. Although these systems perform well in a variety of situations, their performance can be improved if a real-time estimate of the tire-road friction coefficient is available. Existing tire-road friction estimation approaches often require certain levels of vehicle longitudinal and/or lateral motion to satisfy the persistence of excitation condition for reliable estimations. Such excitations may undesirably interfere with vehicle motion controls. This paper presents a novel development and implementation of a real-time tire-road contact parameter estimation methodology using acceleration signals from an intelligent tire. The proposed method characterizes the terrain using the measured frequency response of the tire vibrations and provides the capability to estimate the tire road friction coefficient under extremely lower levels of force utilization. Under higher levels of force excitation (high slip conditions), the increased vibration levels due to the stick/slip phenomenon linked to the tread block vibration modes make the proposed tire vibrations based method unsuitable. Therefore for high slip conditions, a brush model-based nonlinear least squares (NLLS) parameter estimation approach is proposed. Hence an integrated approach using the intelligent tire based friction estimator and the model based estimator gives us the capability to reliably estimate friction for a wider range of excitations. Considering the strong interdependence between the operating road surface condition and the instantaneous forces and moments generated; this real time estimate of the tire-road friction coefficient is expected to play a pivotal role in improving the performance of a number of vehicle control systems. In particular, this paper focuses on the possibility of enhancing the performance of the ABS control systems. In order to achieve the aforementioned objectives, the design and implementation of a fuzzy/sliding mode/proportional integral (fuzzy-SMC-PI (FSP)) control methodology is proposed. The results show significant improvements in the stopping distance of a vehicle equipped with an intelligent tire based FSP controller as compared to a vehicle equipped with a standard ABS.
机译:轮胎与道路之间的接触是车辆加速,减速和转向的关键因素。然而,由于道路状况的改变,驾驶员保持稳定车辆的能力可能受到威胁。在许多情况下,这需要车辆上底盘控制系统的干预。尽管这些系统在各种情况下都能很好地运行,但是如果可以实时估算轮胎-道路摩擦系数,则可以提高其性能。现有的轮胎-道路摩擦力估算方法通常需要一定水平的车辆纵向和/或横向运动,以满足激励条件的持续性,以进行可靠的估算。这样的激励可能不期望地干扰车辆运动控制。本文介绍了使用来自智能轮胎的加速度信号进行实时轮胎-道路接触参数估计方法的新颖开发和实现。所提出的方法使用测得的轮胎振动频率响应来表征地形,并提供了在极低水平的力利用条件下估算轮胎路面摩擦系数的能力。在较高水平的力激励下(高滑移条件),由于与胎面花纹块振动模式相关的粘滞/滑移现象而导致的振动水平增加,因此建议的基于轮胎振动的方法不合适。因此,对于高滑移条件,提出了一种基于画笔模型的非线性最小二乘(NLLS)参数估计方法。因此,使用基于智能轮胎的摩擦估计器和基于模型的估计器的集成方法使我们能够针对更广泛的激励范围可靠地估计摩擦。考虑到工作路面状况与产生的瞬时力和力矩之间的强烈相互依赖关系;轮胎-道路摩擦系数的实时估计有望在改善许多车辆控制系统的性能中发挥关键作用。特别是,本文着重于增强ABS控制系统性能的可能性。为了达到上述目的,提出了一种模糊/滑模/比例积分(fuzzy-SMC-PI(FSP))控制方法的设计与实现。结果表明,与配备标准ABS的车辆相比,配备了基于智能轮胎的FSP控制器的车辆的停车距离有了显着改善。

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