Estimation of the Maximum Tire-Road Friction Coefficient

2003 ◽  
Vol 125 (4) ◽  
pp. 607-617 ◽  
Author(s):  
Steffen Mu¨ller ◽  
Michael Uchanski ◽  
Karl Hedrick
Keyword(s):  
Friction Coefficient ◽  
Estimation Algorithm ◽  
Road Surface ◽  
Measurement Noise ◽  
Misclassification Rate ◽  
The Road ◽  
Subtle Effect ◽  
Road Friction ◽  
Friction Estimation ◽  
Road Friction Coefficient

We develop and test a “slip-based” method to estimate the maximum available tire-road friction during braking. The method is based on the hypothesis that the low-slip, low-μ parts of the slip curve used during normal driving can indicate the maximum tire-road friction coefficient, μmax. We find support for this hypothesis in the literature and through experiments. The friction estimation algorithm uses data from short braking maneuvers with peak accelerations of 3.9 m/s2 to classify the road surface as either dry μmax≈1 or lubricated μmax≈0.6. Significant measurement noise makes it difficult to detect the subtle effect being measured, leading to a misclassification rate of 20%.

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

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Kanwar B. Singh ◽  
Mustafa Ali Arat ◽  
Saied Taheri
Keyword(s):  
Parameter Estimation ◽  
Friction Coefficient ◽  
Control Systems ◽  
Real Time ◽  
Time Estimate ◽  
Slip Conditions ◽  
The Road ◽  
Road Friction ◽  
Friction Estimation ◽  
Road Friction Coefficient

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.

A review on identification methods of road friction coefficient

2021 ◽  
Vol 15 ◽  
Author(s):  
Gengxin Qi ◽  
Xiaobin Fan ◽  
Hao Li
Keyword(s):  
Friction Coefficient ◽  
Autonomous Driving ◽  
Research Direction ◽  
Identification Methods ◽  
Research Status ◽  
The Road ◽  
Road Friction ◽  
Coefficient Measurement ◽  
Estimation System ◽  
Road Friction Coefficient

Background: The development of the tire/road friction coefficient measurement and estimation system has far-reaching significance for the active electronic control safety system of automobiles and is one of the core technologies for autonomous driving in the future. Objective: Estimating the road friction coefficient accurately and in real-time has become the leading research direction. Researchers have used different tools and proposed different algorithms and patents. These methods are widely used to estimate the road friction coefficient or other related parameters. This paper gives a comprehensive description of the research status in the field of road friction coefficient estimation. Method: According to the current research status of Chinese and foreign scholars in the field of road friction coefficient recognition, the recognition methods are mainly divided into two categories: Cause-based and Effect-based. Results: This literature review will discuss the existing two types of identification methods (Cause-based and Effect-based), and the applicable characteristics of each algorithm are analyzed. Conclusion: The two recognition methods are analyzed synthetically, and the development direction of road friction coefficient recognition technology is discussed.

Hierarchical Nonlinear Moving Horizon Estimation of Vehicle Lateral Speed and Road Friction Coefficient

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Chi Jin ◽  
Anson Maitland ◽  
John McPhee
Keyword(s):  
Friction Coefficient ◽  
Numerical Optimization ◽  
Optimization Problems ◽  
Global Optimum ◽  
Moving Horizon Estimation ◽  
The Road ◽  
Nominal Model ◽  
Road Friction ◽  
High Level ◽  
Road Friction Coefficient

Abstract In this paper, we address nonlinear moving horizon estimation (NMHE) of vehicle lateral speed, as well as the road friction coefficient, using measured signals from sensors common to modern series-production automobiles. Due to nonlinear vehicle dynamics, a standard nonlinear moving horizon formulation leads to non-convex optimization problems, and numerical optimization algorithms can be trapped in undesirable local minima, leading to incorrect solutions. To address the challenge of non-convex cost functions, we propose an estimator with a two-level hierarchy. At the high level, a grid search combined with numerical optimization aims to find reference estimates that are sufficiently close to the global optimum. The reference estimates are refined at the low level leading to high-precision solutions. Our algorithm ensures that the estimates converge to the true values for the nominal model without the need for accurate initialization. Our design is tested in simulation with both the nominal model as well as a high-fidelity model of Autonomoose, the self-driving car of the University of Waterloo.

A New Method for Estimating Road Friction Coefficient

2010 ◽  
Vol 139-141 ◽  
pp. 2622-2625
Author(s):  
Fen Lin
Keyword(s):  
Friction Coefficient ◽  
Traffic Safety ◽  
Sliding Mode ◽  
Estimation Algorithm ◽  
Longitudinal Force ◽  
Recursive Least Squares ◽  
Force Estimation ◽  
Road Friction ◽  
Vehicle Activity ◽  
Road Friction Coefficient

Road friction coefficient is a critical component in traffic safety. The estimation of tire–road friction coefficient at tires allows the control algorithm in vehicle activity system to adapt to external driving conditions. This paper develops a new tire–road friction coefficient estimation algorithm based on tire longitudinal force estimation and tire slip estimation. Vehicle tire longitudinal forces are estimated by sliding mode observer combined with Kalman filter. Based on the tire forces estimation, road friction coefficient is estimated by recursive least squares algorithm (RLS). The test conditions which contain different friction level road are established in ADAMS/Car. The conclusions validate the reliability and efficiency of the proposed method for estimating the friction coefficient in different adhesion level roads. The research also indicates the theory of slip slope can also be reappeared in virtual experiment based on ADAMS.

scholarly journals Optimal Spacing Policy for Vehicle Platoon Control with Road-Friction Coefficient

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Lei Zuo ◽  
Duo Meng ◽  
Jinqi Zhang
Keyword(s):  
Friction Coefficient ◽  
Sliding Mode ◽  
The Road ◽  
Optimization Framework ◽  
Control Scheme ◽  
Road Friction ◽  
Vehicle Platoon ◽  
Optimal Spacing ◽  
The Stability ◽  
Road Friction Coefficient

This paper investigates the vehicle platoon control problems, in which the road-friction coefficient is taken into consideration. In order to improve the vehicle platoon safety in various road-friction conditions, an optimal spacing policy is proposed for the vehicle platoon. In detail, an intervehicle space optimization framework is developed by using a safety cost function and the gradient decent method. In this way, the optimal intervehicle spacing headway is presented such that the vehicle can be safely driven to the desired platoon under various road-friction conditions. Then, based on the proposed optimal spacing policy, we transform this optimal spacing vehicle platoon control problem into a moving target tracking problem. An adaptive distributed integrated sliding mode (DISM)-based vehicle platoon control scheme is proposed such that the vehicles can effectively follow the presented optimal spacing platoon. Moreover, the stability of the proposed vehicle platoon system is strictly analyzed and numerical simulations are provided to verify the proposed approaches.

scholarly journals Study on Road Friction Database for Automated Driving - Fundamental Consideration of Measuring Device for Road Friction Database -

2021 ◽  
Author(s):  
Tetsunori Haraguchi ◽  
Ichiro Kageyama ◽  
Yukiyo Kuriyagawa ◽  
Tetsuya Kaneko ◽  
Motohiro Asai ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Traffic Safety ◽  
Surface Condition ◽  
Automated Driving ◽  
Friction Coefficients ◽  
Measuring Device ◽  
The Road ◽  
Road Friction ◽  
Road Friction Coefficient ◽  
Fundamental Consideration

This research deals with the possibility for construction of the database on the braking friction coefficient for actual roads from the viewpoint of traffic safety especially for automated driving such as level 4 or higher. In an automated driving such levels, the controller needs to control the vehicle, but the road surface condition, especially the road friction coefficient on wet roads, snowy or icy roads, changes greatly, and in some cases, changes by almost one order. Therefore, it is necessary for the controller to constantly collect environment information such as the road friction coefficients and prepare for emergencies such as obstacle avoidance. However, at present, the measurement of the road friction coefficients is not systemically performed, and a method for accurately measuring has not been established. In order to improve this situation, this study examines a method for continuously measurement for the road friction characteristics such as μ-s characteristics.

Robust adaptive anti-slip regulation controller for a distributed-drive electric vehicle considering the driver’s intended driving torque

2017 ◽  
Vol 232 (4) ◽  
pp. 562-576 ◽  
Author(s):  
Zhuoping Yu ◽  
Renxie Zhang ◽  
Xiong Lu ◽  
Chi Jin ◽  
Kai Sun
Keyword(s):  
Friction Coefficient ◽  
Electric Vehicle ◽  
State Feedback Control ◽  
Slip Ratio ◽  
The Road ◽  
Road Friction ◽  
Distributed Drive Electric Vehicle ◽  
Robust Adaptive ◽  
Driving Torque ◽  
Road Friction Coefficient

A robust adaptive anti-slip regulation controller which consists of two components, namely a road friction coefficient estimator and a wheel dynamics controller, is designed for distributed-drive electric vehicles. The road friction coefficient estimator is based on the latest non-affine parameter estimation theory to achieve the peak road friction coefficient. Also, working conditions for the road friction coefficient estimator are proposed to avoid the estimation error caused by a small slip ratio. According to the results of the road friction coefficient estimator, the desired reference slip ratio is obtained and the key parameters of the robust adaptive anti-slip regulation controller are modified to make sure that the road conditions can be made full use of. Then, according to the desired reference slip ratio, a state feedback control law with a conditional integrator is designed on the basis of the Lyapunov stability theory for a wheel dynamics controller by analysis of the non-linear characteristics of the tyres and the driver’s intended driving torque and constraints from the ground–tyre adhesion. In addition, it achieves smooth switching between optimal driving and the driver’s intended driving torque rather than normal switching logic. Multi-condition simulations and experiments show that the controller is adaptive to different road conditions, can improve the driving efficiency of the vehicle and can ensure stability of the vehicle. Finally, with comparative experiments, the distributed-drive electric vehicle with a robust adaptive anti-slip regulation controller proves to be more efficient than the traditional vehicle with a traditional anti-slip regulation controller.

Active Vibration Cancellation for Tire Road Friction Estimation

2009 ◽  
Author(s):  
Gurkan Erdogan ◽  
Lee Alexander ◽  
Rajesh Rajamani
Keyword(s):  
Friction Coefficient ◽  
Force Sensor ◽  
Measured Signal ◽  
The Road ◽  
Road Friction ◽  
Active Vibration ◽  
Friction Estimation ◽  
Estimation System ◽  
Active Vibration Cancellation ◽  
Adaptive Feedforward

This paper focuses on the development and experimental evaluation of a novel adaptive feedforward vibration cancellation based friction estimation system. The friction estimation utilizes a small instrumented redundant wheel on the vehicle. Unlike other systems previously documented in literature, the developed system can provide a continuous measurement of the friction coefficient under all vehicle maneuvers, even when the longitudinal and lateral accelerations are both zero. A key challenge in the development of the estimation system is the need to remove the influence of vibrations and the influence of vehicle maneuvers from the measured signal of a force sensor. An adaptive feedforward algorithm based on the use of accelerometer signals as reference inputs is developed. The parameters of the feedforward model estimated by the adaptive algorithm themselves serve to determine the value of the friction coefficient. Detailed experimental results are presented on a skid pad wherein the road surface changes from dry asphalt to ice.

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