Abstract
The road friction coefficient is a key parameter for autonomous vehicles and vehicle dynamic control. With the development of autonomous vehicles, increasingly, more environmental perception sensors are being installed on vehicles, which means that more information can be used to estimate the road friction coefficient. In this paper, a nonlinear observer aided by vehicle lateral displacement information for estimating the road friction coefficient is proposed. First, the tire brush model is modified to describe the tire characteristics more precisely in high friction conditions using tire test data. Then, on the basis of vehicle dynamics and a kinematic model, a nonlinear observer is designed, and the self-aligning torque of the wheel, lateral acceleration, and vehicle lateral displacement are used to estimate the road friction coefficient during steering. Finally, slalom tests and DLC (Double Line Change) tests in high friction conditions are conducted to verify the proposed estimation algorithm. Test results showed that the proposed method performs well during steering and the estimated road friction coefficient converges to the reference value rapidly.
Highlights
Vehicle safety-related state estimation [1,2,3] and control systems [4,5,6] have received much attention in recent decades
The road friction coefficient is a key parameter for vehicle dynamic control systems [7,8], because it can reflect the dynamic motion limitations to a certain extent [9]
We introduced vehicle lateral displacement, which is based on the relationship between road friction and the self-aligning torque of the front axle, to the framework of road friction coefficient estimation
Summary
Vehicle safety-related state estimation [1,2,3] and control systems [4,5,6] have received much attention in recent decades. The road friction coefficient is a key parameter for vehicle dynamic control systems [7,8], because it can reflect the dynamic motion limitations to a certain extent [9]. Assistant System) functions are being implemented by automated systems, which means that driving and braking forces and steering angles need to be calculated and controlled by control units, such as ACC (Adaptive Cruise Control) and LKA (Lane Keep Assistant). An accurate road friction coefficient provides the automated system with the current motion limitation of the vehicle
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