Robust estimation of maximum tire-road friction coefficient considering road surface irregularity

2016 ◽  
Vol 17 (3) ◽  
pp. 415-425 ◽  
Author(s):  
K. Han ◽  
Y. Hwang ◽  
E. Lee ◽  
S. Choi
2021 ◽  
Vol 11 (11) ◽  
pp. 4891
Author(s):  
Yu-Min Lin ◽  
Bo-Chiuan Chen

Steering has more potential than braking to prevent rear-end collisions at higher relative velocities. A path tracking controller based on multi-input multi-output (MIMO) model predictive control (MPC) is proposed to enhance the handling performance of autonomous emergency steering in this paper. A six-state MIMO bicycle model including actuator dynamics of steering and differential braking is used for model prediction. Two control inputs are front wheel steering angle and direct yaw moment. Two model outputs are lateral displacement and heading angle. According to the work load ratios at four wheels, control allocation is used to determine the optimal braking force distribution to prevent tire force saturation. The performance of a single-input single-output (SISO) MPC that uses only steering angle control to track the lateral displacement of the desired path is employed to benchmark the performance of the proposed algorithm. Simulation results show that both SISO MPC and MIMO MPC can track the path on nominal road surface with high road friction coefficient of 0.9. For a road surface with medium road friction coefficient of 0.7, the SISO MPC is unable to track the path and loses directional stability. However, the MIMO MPC can still track the path and demonstrate robust path tracking and handling enhancement against model uncertainty due to reduced road friction.


2003 ◽  
Vol 125 (4) ◽  
pp. 607-617 ◽  
Author(s):  
Steffen Mu¨ller ◽  
Michael Uchanski ◽  
Karl Hedrick

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%.


2014 ◽  
Vol 8 (1) ◽  
pp. 292-296
Author(s):  
Zhi-Guo Zhao ◽  
Min Chen ◽  
Nan Chen ◽  
Yong-Bing Zhao ◽  
Xin Chen

The lateral security of heavy vehicle in deteriorative weather is one of the main causes of accidents of vehicles on roads. Road safety has become a subject of great concern to institutions of higher education and scientific research institutions. There are important theoretical and practical significances to explore applicable and effective lateral safety warning methods of heavy vehicles. One of the purposes of this paper is to provide a good theoretical basis for the core technology of heavy vehicle safety features for our country's independent research and development. Aiming at the issue of lateral security of heavy vehicle for road conditions in deteriorative weather, this paper constructs the framework of the lateral security pre-warning system of heavy vehicles based on cooperative vehicle infrastructure. Moreover, it establishes vehicle lateral security statics model through analysis of the force of the car in the slope with section bending and states the parameters of vehicles for no rollover. The side slip is indexed to calculate critical speed of vehicles in a bend. This paper also analyzes the influence of road friction coefficient, the road gradient and the turning radius on the lateral security of the vehicle with critical speed on the asphalt pavement with surface conditions ranging from wet, dry, snowing or icy. The calculation results show that the bad weather road conditions, road friction coefficient and turning radius have obvious influence on the lateral security critical speed. Experimental results indicate that the critical speed error warning is within 4% and it meets the design requirements.


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