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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.
Hahn et al. (2002) studied this question.