scholarly journals Adaptive Nonlinear Tire-Road Friction Force Estimation for Vehicular Systems Based on a Novel Differentiable Friction Model

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Zhi-Jun Fu ◽  
Wei-Dong Xie ◽  
Xiao-Bin Ning
Keyword(s):  
Friction Force ◽  
Estimation Algorithm ◽  
Friction Model ◽  
Lyapunov Theory ◽  
Nonlinear Observer ◽  
Estimation Methods ◽  
Vehicle Speed ◽  
Force Estimation ◽  
Observer Error ◽  
Road Friction

A novel adaptive nonlinear observer-based parameter estimation scheme using a newly continuously differentiable friction model has been developed to estimate the tire-road friction force. The differentiable friction model is more flexible and suitable for online adaptive identification and control with the advantage of more explicit parameterizable form. Different from conventional estimation methods, the filtered regression estimation parameter is introduced in the novel adaptive laws, which can guarantee that both the observer error and parameter error exponentially converge to zero. Lyapunov theory has been used to prove the stability of the proposed methods. The effectiveness of the estimation algorithm is illustrated via a bus simulation model in the Trucksim software and simulation environment. The relatively accurate tire-road friction force was estimated just by the easily existing sensors signals wheel rotational speed and vehicle speed and the proposed method also displays strong robustness against bounded disturbances.

An Adaptive Nonlinear Differentiable Friction Modeling for Tire-Road Friction Estimation

2015 ◽  
Author(s):  
Zhi-Jun Fu ◽  
Subhash Rakheja ◽  
Wen-Fang Xie ◽  
Xiao-Bin Ning ◽  
Wei-Dong Xie
Keyword(s):  
Parameter Estimation ◽  
Estimation Error ◽  
Friction Model ◽  
Least Square ◽  
Nonlinear Observer ◽  
Accurate Estimation ◽  
Vehicle Speed ◽  
Recursive Least Square ◽  
Friction Modeling ◽  
Road Friction

In this paper, a differentiable friction model is proposed to estimate the longitudinal tire-road friction force of vehicle systems. A novel adaptive nonlinear observer-based parameter estimation scheme has been developed to estimate the parameters of friction model, which requires the signals from the existing sensors signals such as wheel rotational speed and vehicle speed. Different from conventional gradient and recursive least square (RLS) methods, the filtered regression parameter estimation error is introduced in the novel adaptive laws, which can guarantee the observer error convergence to zero and the estimated parameter also convergence to their real value. The Lyapunov method is used to prove the stability of the proposed methods. The robustness of the developing method against bounded disturbances is also proved. Simulation results illustrate that the proposed method can realize relatively accurate estimation of the friction with variations in speed and road gradient.

Vehicle State and Friction Force Estimation Based on FPGA

2013 ◽  
Vol 336-338 ◽  
pp. 999-1002
Author(s):  
Lin Hui Zhao ◽  
Zhi Yuan Liu
Keyword(s):  
Friction Force ◽  
Estimation Algorithm ◽  
Nonlinear Observer ◽  
Force Estimation ◽  
Verilog Hdl ◽  
Description Language ◽  
Computational Performance ◽  
Field Programmable ◽  
Hardware Description ◽  
System On Programmable Chip

In order to improve the computational performance of the nonlinear observer for vehicle state and friction force estimation, two novel implementation schemes in Verilog Hardware Description Language (HDL) and System on Programmable Chip (SoPC) is proposed based on Field Programmable Gate Array (FPGA). Firstly, the parallelism analysis of the vehicle state and friction force estimation algorithm is provided. Then, the Verilog HDL and SoPC implementation schemes are presented respectively based on the analysis results. Finally, a testing platform is built to evaluate the functionality and the computational performance of the implementation schemes. The experimental results show that the proposed schemes all have high precision and computational efficiency for vehicle state and friction force estimation.

Effect of Load-Dependent Friction on the Estimation of Rack Force in Electric Power-Assisted Steering System

2019 ◽  
Vol 141 (11) ◽  
Author(s):  
Yijun Li ◽  
Taehyun Shim ◽  
Dexin Wang ◽  
Timothy Offerle
Keyword(s):  
Electric Power ◽  
A Priori ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Steering System ◽  
Estimation Methods ◽  
Current Steering ◽  
Force Estimation ◽  
Operation Conditions ◽  
Friction Estimation

The rack force is valuable information for a vehicle dynamics control system, as it relates closely to the road conditions and steering feel. Since there is no direct measurement of rack force in current steering systems, various rack force estimation methods have been proposed to obtain the rack force information. In order to get an accurate rack force estimate, it is important to have knowledge of the steering system friction. However, it is hard to have an accurate value of friction, as it is subject to variation due to operation conditions and material wear. Especially for the widely used column-assisted electric power steering (C-EPAS) system, the load-dependent characteristic of its worm gear friction has a significant effect on rack force estimation. In this paper, a rack force estimation method using a Kalman filter and a load-dependent friction estimation algorithm is introduced, and the effect of C-EPAS friction on rack force estimator performance is investigated. Unlike other rack force estimation methods, which assume that friction is known a priori, the proposed system uses a load-dependent friction estimation algorithm to determine accurate friction information in the steering system, and then a rack force is estimated using the relationship between steering torque and angle. The effectiveness of this proposed method is verified by carsim/simulink cosimulation.

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.

Observer-based friction force estimation for brake system under low-frequency vibration

2021 ◽  
pp. 107754632110004
Author(s):  
Lu Qian ◽  
Xingwei Zhao
Keyword(s):  
Friction Force ◽  
Low Frequency ◽  
Brake System ◽  
Estimation Methods ◽  
Force Estimation ◽  
Stick Slip ◽  
Modeling Methods ◽  
Low Frequency Vibration ◽  
Stick Slip Motion ◽  
Slip Motion

Creep groan is a low-frequency vibration, which is produced by the stick–slip motion from the pad–disc contact in the brake. Friction plays a key role in generating the stick–slip motion. However, directly measuring the friction force in an actual brake system is difficult. Therefore, force estimation methods are proposed to estimate the friction force based on unknown input observers. A proportional integral observer is applied to estimate the friction force amplitude from the torsional angle of the driven shaft. An approximate H2 observer is designed to distinguish the stick region and slip region from the acceleration of the pad. Different from modeling methods, designing observers do not introduce modeling deviation and have a relatively low requirement on parameter identification. In addition, the observer methods can extract more detailed information of friction force than modeling methods. The observed friction force can be considered an index to evaluate the severity of the brake defect. The performance and effectiveness of the proposed methods are confirmed by experiments on a brake test rig.

Transparency performance improvement for multi-master multi-slave teleoperation systems with external force estimation

2017 ◽  
Vol 40 (13) ◽  
pp. 3851-3859 ◽  
Author(s):  
Farhad Azimifar ◽  
Saman Ahmadkhosravi Rozi ◽  
Ahmad Saleh ◽  
Iman Afyouni
Keyword(s):  
Control Strategy ◽  
Closed Loop ◽  
Estimation Algorithm ◽  
Lyapunov Theory ◽  
Shared Environment ◽  
Force Estimation ◽  
Teleoperation System ◽  
Common Control ◽  
Control Scheme ◽  
External Forces

Cooperative teleoperation combines two traditional areas of robotics, that is, teleoperation and collaborative manipulation. Cooperative telerobotic systems consist of multiple pairs of master and slave robotic manipulators operating in a shared environment. The most common control frameworks for nonlinear systems, that is, Proportional Derivative (PD) controllers, possess considerable deficiency in contact motion. In this paper, a novel control scheme is proposed for a nonlinear bilateral cooperative teleoperation system with time delay. In addition to position and velocity signals, force signals are employed in the control strategy. This modification significantly enhances the poor transparency when the slave robots are in collision with the environment. To cope with external forces measurement, a modified force estimation algorithm is proposed to estimate human and environment forces. The closed loop stability of the nonlinear cooperative teleoperation system with the proposed control scheme is investigated using the Lyapunov theory. The main achievement of this research is the stability of the closed loop cooperative teleoperation system in the presence of estimated operator and environmental forces. In addition, it is theoretically and experimentally proved that force reflection occurs and transparency is improved at the same time. Experimental results demonstrate the efficiency of the presented control strategy in free motion as well as when the slave robots are in contact with the environment.

Performance analysis in delayed nonlinear bilateral teleoperation systems by force estimation algorithm

2017 ◽  
Vol 40 (5) ◽  
pp. 1637-1644
Author(s):  
Farhad Azimifar ◽  
Kamran Hassani ◽  
Amir Hossein Saveh ◽  
Farhad Tabatabai Ghomshe
Keyword(s):  
Closed Loop ◽  
Force Measurement ◽  
Estimation Algorithm ◽  
Lyapunov Theory ◽  
Bilateral Teleoperation ◽  
Force Estimation ◽  
Teleoperation System ◽  
Control Scheme ◽  
Teleoperation Systems ◽  
System With Time Delay

This paper establishes a novel control strategy for a nonlinear bilateral teleoperation system with time delay. Besides position and velocity signals, force signals are additionally utilized in the control scheme. This modification significantly improves the poor transparency during contact with the environment. To eliminate the external force measurement, a force estimation algorithm is proposed for the master and slave robots. The closed loop stability of the nonlinear teleoperation system with the proposed control scheme is investigated through the Lyapunov theory. Furthermore, it is theoretically and experimentally proved that force reflection occurs and transparency is enhanced simultaneously. Consequently, experimental results verify the efficiency of the new control scheme in free motion and during collision of the slave robot with the environment.

Neural network based tire/road friction force estimation

2008 ◽  
Vol 21 (3) ◽  
pp. 442-456 ◽  
Author(s):  
Jadranko Matuško ◽  
Ivan Petrović ◽  
Nedjeljko Perić
Keyword(s):  
Neural Network ◽  
Friction Force ◽  
Force Estimation ◽  
Road Friction
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