A Beta-Less Approach for Vehicle Cornering Stiffness Estimation Under Varying Road Friction

Modern vehicles are equipped with a growing amount of advanced driver assistance functions (ADAS), such as adaptive cruise control or collision avoidance systems. These functions heavily rely on the current state of the vehicle. Particularly for lateral vehicle dynamics functions, the state of the tires has a crucial influence. For moderate driving scenarios, the vehicle lateral tire forces are mainly described by the tire cornering stiffnesses, which give a linear relation between tire slip angles and the resulting lateral tire forces. However, the tire cornering stiffnesses heavily depend on the type of tire and on many parameters, most significantly the tire vertical load, the tire wear and the tire pressure. As such changes in tire cornering stiffness can lead to a completely different vehicle behavior, it is essential to obtain current cornering stiffness estimates for the application of ADAS. Thus, this paper proposes a combined beta-less approach for vehicle cornering stiffness and road-friction coefficient estimation based on a nonlinear tire model, which solely makes use of typical vehicle in-series sensors. Vehicle measurements on dry road as well as on ice show the effectiveness of the proposed method.