A comparative study of the recursive least squares and fuzzy logic estimation methods for the measurement of road adhesion coefficient.

Vehicle active safety system is the hotspot of current research and development, and the road adhesion coefficient is one of the essential parameters in the development of automobile active safety system, which plays a pivotal role in automobile safety. To improve the real-time performance and accuracy of the road adhesion coefficient, this paper proposes different control methods and compares and analyzes them. To accurately estimate the road adhesion coefficient in real-time, an eight-degree-of-freedom vehicle model was adopted in this paper. According to the tire torque and wheel speed, the adhesion coefficient was estimated based on the second-order nonlinear extended state observer. The experimental data, such as slip rate, using the improved tire model, is based on the recursive least squares method with forgetting factor and fuzzy logic algorithm real-time of tire-road friction coefficient estimation. The results show that the observer can effectively observe utilisation adhesion coefficient, and both control algorithms can estimate the road adhesion coefficient in real-time, effectively and quickly. On different roads, the use of the recursive least squares algorithm resulted in higher estimation accuracy, better robustness, and better control effect than using a fuzzy logic algorithm. [ABSTRACT FROM AUTHOR]