Abstract
This study presents a real-time capable methodology for quantifying the hydroplaning risk of a passenger car tire using data from an intelligent tire system. An analytical water lift force formulation is applied to convert measured peak lift force values into longitudinal water velocity. Based on the water velocity and groove dimensions, the intake flow rate that the tire must evacuate is estimated. Hydroplaning risk is then defined as the ratio between the intake flow rate and the maximum flow capacity of the tire before total hydroplaning occurs. Experimental investigations under real-world conditions were carried out at 45 mph and 65 mph, yielding average hydroplaning risk values of 12.6% and 21.3%. The proposed model was validated by performing hydroplaning tests under a controlled water depth of 1 mm at Michelin Laurens Proving Grounds. The hydroplaning risk values computed by the intelligent tire system were compared with reference data from the literature obtained under similar test conditions. Additionally, the critical hydroplaning speed of the test tire was estimated and compared against predictions from established numerical models, such as those proposed by Gengenbach and Spitzhüttl. The methodology is confirmed as a reliable algorithm for real-time hydroplaning risk monitoring with the potential to improve vehicle safety.