Slip-Slope Estimation of Mutative Road Friction Coefficient Based on Unscented Particle Filter

2012 ◽  
Vol 249-250 ◽  
pp. 337-342
Author(s):  
Fen Lin ◽  
Chao Huang
Keyword(s):  
Friction Coefficient ◽  
Particle Filter ◽  
Dynamic Model ◽  
Estimation Method ◽  
Accurate Information ◽  
Vehicle Dynamic ◽  
Unscented Particle Filter ◽  
Road Friction ◽  
Vehicle Dynamic Model ◽  
Road Friction Coefficient

The accurate information of road friction coefficient allows the control algorithm in vehicle activity system to adapt to external driving conditions. This paper developed a slip-slope friction coefficient estimation method based on Unscented Particle Filter. A 7-DOF non-linear vehicle dynamic model was established. The normal force of tire was approximately calculated from the vehicle dynamic model; the slip and longitudinal force of tire were estimated through a combination of tire mechanical model and UPF(Unscented Particle Filter) method. Finally slip-slopes of different adhesion level roads was obtained. Through virtual test environment in ADAMS/Car, the estimation method proposed was verified to be effective and reliable under various road condition. From the method the relationships between the slip-slope and road friction coefficient are achieved.

Adaptive Unified Monitoring System Design for Tire-Road Information

2019 ◽  
Vol 141 (7) ◽  
Author(s):  
Shuo Cheng ◽  
Ming-ming Mei ◽  
Xu Ran ◽  
Liang Li ◽  
Lin Zhao
Keyword(s):  
Friction Coefficient ◽  
Monitoring System ◽  
Estimation Method ◽  
Recursive Least Squares ◽  
Vehicle Body ◽  
Friction Forces ◽  
Road Friction ◽  
Tire Forces ◽  
Tire Friction ◽  
Road Friction Coefficient

Knowledge of the tire-road information is not only very crucial in many active safety applications but also significant for self-driving cars. The tire-road information mainly consists of tire-road friction coefficient and road-tire friction forces. However, precise measurement of tire-road friction coefficient and tire forces requires expensive equipment. Therefore, the monitoring of tire-road information utilizing either accurate models or improved estimation algorithms is essential. Considering easy availability and good economy, this paper proposes a novel adaptive unified monitoring system (AUMS) to simultaneously observe the tire-road friction coefficient and tire forces, i.e., vertical, longitudinal, and lateral tire forces. First, the vertical tire forces can be calculated considering vehicle body roll and load transfer. The longitudinal and lateral tire forces are estimated by an adaptive unified sliding mode observer (AUSMO). Then, the road-tire friction coefficient is observed through the designed mode-switch observer (MSO). The designed MSO contains two modes: when the vehicle is under driving or brake, a slip slope method (SSM) is used, and a recursive least-squares (RLS) identification method is utilized in the SSM; when the vehicle is under steering, a comprehensive friction estimation method is adopted. The performance of the proposed AUMS is verified by both the matlab/simulinkCarSim co-simulation and the real car experiment. The results demonstrate the effectiveness of the proposed AUMS to provide accurate monitoring of tire-road information.

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