Development of an Intelligent Instrumented Tire for Real-Time Hydroplaning Risk Estimation

<div>This study introduces an innovative intelligent tire system capable of estimating the risk of total hydroplaning based on water pressure measurements within the tread grooves. Dynamic hydroplaning represents an important safety concern influenced by water depth, tread design, and vehicle longitudinal speed. Existing intelligent tire systems primarily assess hydroplaning risk using the water wedge effect, which occurs predominantly in deep water conditions. However, in shallow water, which is far more prevalent in real-world scenarios, the water wedge effect is absent at higher longitudinal speeds, which could make existing systems unable to reliably assess the total hydroplaning risk. Groove flow represents a key factor in hydroplaning dynamics, and it is governed by two mechanisms: water interception rate and water wedge pressure. In both the shallow water and deep water cases, the groove water flow will increase as a result of increasing the longitudinal speed of the vehicle for a constant water depth. Therefore, the water pressure in the tread grooves will also increase as the longitudinal speed of the vehicle approaches the critical hydroplaning speed. Unlike conventional systems, the proposed intelligent tire design utilizes the amplitude and shape of the measured pressure signals from the tread grooves for estimating the total hydroplaning risk in both shallow and deep water conditions. Experimental results indicate that peak groove water pressure increases with the risk of total hydroplaning. Furthermore, the overall shape of the pressure signal will also be influenced by the total hydroplaning risk. By addressing the limitations of current intelligent tire systems, the proposed intelligent tire design offers a robust solution for real-time total hydroplaning risk estimation across diverse driving conditions.</div>