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

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...

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Bibliographic Details
Published in:IEEE transactions on control systems technology 2002-05, Vol.10 (3), p.331-343
Main Authors: Jin-Oh Hahn, Rajamani, R., Alexander, L.
Format: Article
Language:English
Subjects:
Adaptive control
Algorithms
Applied sciences
Automatic control
Collision avoidance
Computer science
control theory
systems
Control system analysis
Control systems
Control theory. Systems
Dynamical systems
Dynamics
Exact sciences and technology
Friction
Global positioning systems
GPS
Mathematical models
Modelling and identification
Programmable control
Road vehicles
Roads
Slip
Stability
Studies
Tires
Wheels
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Summary: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.
ISSN:1063-6536
1558-0865
DOI:10.1109/87.998016