Development and Verification of the Tire-Road Friction Estimation Algorithm for Antilock Braking SystemReport as inadecuate

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Mathematical Problems in Engineering - Volume 2014 2014, Article ID 786492, 15 pages -

Research Article

State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China

Key Laboratory of Bionic Engineering of Ministry of Education, Jilin University, Changchun 130022, China

Received 8 June 2014; Revised 6 August 2014; Accepted 6 August 2014; Published 28 September 2014

Academic Editor: Ebrahim Momoniat

Copyright © 2014 Jian Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Road friction information is very important for vehicle active braking control systems such as ABS, ASR, or ESP. It is not easy to estimate the tire-road friction forces and coefficient accurately because of the nonlinear system, parameters uncertainties, and signal noises. In this paper, a robust and effective tire-road friction estimation algorithm for ABS is proposed, and its performance is further discussed by simulation and experiment. The tire forces were observed by the discrete Kalman filter, and the road friction coefficient was estimated by the recursive least square method consequently. Then, the proposed algorithm was analysed and verified by simulation and road test. A sliding mode based ABS with smooth wheel slip ratio control and a threshold based ABS by pulse pressure control with significant fluctuations were used for the simulation. Finally, road tests were carried out in both winter and summer by the car equipped with the same threshold based ABS, and the algorithm was evaluated on different road surfaces. The results show that the proposed algorithm can identify the variation of road conditions with considerable accuracy and response speed.

Author: Jian Zhao, Jin Zhang, and Bing Zhu



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