Necessity of the Tire Temperature-Dependant Parameters in Vehicle Virtual Sensing

Vehicle state estimation plays a crucial role in the design and development of advanced systems for vehicle control and autonomous driving applications. In this context, the knowledge of vehicle side slip angle is required to optimize lateral dynamics control, improving the overall handling performance. On one hand, the direct measurement of lateral velocity can only be provided by employing sophisticated and expensive onboard sensors. On the other hand, the vehicle system and, in particular, the tires can significantly modify their behaviour through time due to temperature, pressure and wear influences, thus modifying both the vehicle handling behaviour and the parameters of the installable control logic. For this reason, the authors propose an innovative estimation method, combining the vehicle mathematical implementation with a double-track model enriched with virtual observations obtained through a kinematic observer. To validate its applicability in contexts covering a wide range of tire thermodynamic conditions, the proposed estimation approach has been integrated with a multiphysical tire formulation, proposed by the authors in the previous studies, able to take into account of temperature and pressure effect on the tire dynamic response. The results have been analysed in terms of the vehicle sideslip angle acquired in a dedicated experimental campaign comparing the accuracy of the proposed approach to the commonly adopted one, not accounting for temperature and pressure influences.