GPS-based real-time identification of tire-road friction coefficient

Jin Oh Hahn; Rajesh Rajamani; Lee Alexander

doi:10.1109/87.998016

GPS-based real-time identification of tire-road friction coefficient

Jin Oh Hahn, Rajesh Rajamani, Lee Alexander

Research output: Contribution to journal › Article › peer-review

199 Scopus citations

Abstract

Vehicle control systems such as collision avoidance, adaptive cruise control, and automated lane-keeping systems as well as ABS and stability control systems can benefit significantly from being made "road-adaptive.". The estimation of tire-road friction coefficient at the wheels allows the control algorithm in such systems to adapt to external driving conditions. This paper develops a new tire-road friction coefficient estimation algorithm based on measurements related to the lateral dynamics of the vehicle. A lateral tire force model parameterized as a function of slip angle, friction coefficient, normal force and cornering stiffness is used. A real-time parameter identification algorithm that utilizes measurements from a differential global positioning system (DGPS) system and a gyroscope is used to identify the tire-road friction coefficient and cornering stiffness parameters of the tire. The advantage of the developed algorithm is that it does not require large longitudinal slip in order to provide reliable friction estimates. Simulation studies indicate that a parameter convergence rate of 1 s can be obtained. Experiments conducted on both dry and slippery road indicate that the algorithm can work very effectively in identifying a slippery road.

Original language	English (US)
Pages (from-to)	331-343
Number of pages	13
Journal	IEEE Transactions on Control Systems Technology
Volume	10
Issue number	3
DOIs	https://doi.org/10.1109/87.998016
State	Published - May 2002

Bibliographical note

Funding Information:
Manuscript received September 5, 2000; revised May 27, 2001. Manuscript received in final form January 14, 2002. Recommended by Associate Editor M. Jankovic. This work was supported in part by the Minnesota Department of Transportation and by the ITS-Institute, University of Minnesota. The authors are with the Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455 USA (e-mail: rajamani@me.umn.edu). Publisher Item Identifier S 1063-6536(02)03418-8.

Keywords

Friction identification
Global positioning system (GPS)
Parameter identification
Tire-road friction
Vehicle dynamics

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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keywords = "Friction identification, Global positioning system (GPS), Parameter identification, Tire-road friction, Vehicle dynamics",

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GPS-based real-time identification of tire-road friction coefficient

Abstract

Bibliographical note

Keywords

UN SDGs

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