Linearized Recursive Least Squares Methods for Real-Time Identification of Tire–Road Friction Coefficient

2013 ◽  
Vol 62 (7) ◽  
pp. 2906-2918 ◽  
Author(s):  
Mooryong Choi ◽  
Jiwon J. Oh ◽  
Seibum B. Choi
Keyword(s):  
Friction Coefficient ◽  
Least Squares ◽  
Real Time ◽  
Recursive Least Squares ◽  
Road Friction ◽  
Real Time Identification ◽  
Road Friction Coefficient

A New Method for Estimating Road Friction Coefficient

2010 ◽  
Vol 139-141 ◽  
pp. 2622-2625
Author(s):  
Fen Lin
Keyword(s):  
Friction Coefficient ◽  
Traffic Safety ◽  
Sliding Mode ◽  
Estimation Algorithm ◽  
Longitudinal Force ◽  
Recursive Least Squares ◽  
Force Estimation ◽  
Road Friction ◽  
Vehicle Activity ◽  
Road Friction Coefficient

Road friction coefficient is a critical component in traffic safety. The estimation of tire–road friction coefficient at tires allows the control algorithm in vehicle activity system to adapt to external driving conditions. This paper develops a new tire–road friction coefficient estimation algorithm based on tire longitudinal force estimation and tire slip estimation. Vehicle tire longitudinal forces are estimated by sliding mode observer combined with Kalman filter. Based on the tire forces estimation, road friction coefficient is estimated by recursive least squares algorithm (RLS). The test conditions which contain different friction level road are established in ADAMS/Car. The conclusions validate the reliability and efficiency of the proposed method for estimating the friction coefficient in different adhesion level roads. The research also indicates the theory of slip slope can also be reappeared in virtual experiment based on ADAMS.

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