Wireless Piezoelectric Sensor for the Measurement of Tire Deformations and the Estimation of Slip Angle

2009 ◽  
Author(s):  
Gurkan Erdogan ◽  
Lee Alexander ◽  
Rajesh Rajamani
Keyword(s):  
Friction Coefficient ◽  
Piezoelectric Sensor ◽  
Slip Angle ◽  
Lateral Deformation ◽  
Test Rig ◽  
Slip Ratio ◽  
Lateral Deflection ◽  
Road Friction ◽  
Tire Forces ◽  
Road Friction Coefficient

This paper introduces a wireless piezoelectric tire sensor whose readings can be utilized for the estimation of various tire variables such as slip angle, slip ratio, tire forces and tire road friction coefficient. In this paper, the proposed sensor is demonstrated for the estimation of tire slip angle. Lateral deformation of the tire is decoupled from radial and longitudinal tire deformations using a special sensor design. The decoupled lateral deflection profile of the tire is employed to estimate the slip angle. A new tire test rig is constructed to experimentally evaluate the performance of the developed sensor. Results show that the tire sensor can accurately estimate slip angles up to values of 5.0 degrees.

Measurement of Uncoupled Lateral Carcass Deflections With a Wireless Piezoelectric Sensor and Estimation of Tire Road Friction Coefficient

2010 ◽  
Author(s):  
Gurkan Erdogan ◽  
Lee Alexander ◽  
Rajesh Rajamani
Keyword(s):  
Friction Coefficient ◽  
Leading Edge ◽  
Piezoelectric Sensor ◽  
Lateral Force ◽  
Slip Angle ◽  
Contact Patch ◽  
Tire Force ◽  
Coefficient Estimation ◽  
Road Friction ◽  
Road Friction Coefficient

A new tire-road friction coefficient estimation approach based on lateral carcass deflection measurements is proposed. The unique design of the developed wireless piezoelectric sensor decouples lateral carcass deformations from radial and tangential carcass deformations. The estimation of the tire-road friction coefficient depends on the estimation of the slip angle and the lateral tire force. The tire slip angle is estimated as the slope of the lateral deflection curve at the leading edge of the contact patch. The lateral tire force is obtained by using a parabolic relationship with the lateral deflections in the contact patch. The estimated slip angle and lateral force are then plugged into a tire brush model to estimate the tire-road friction coefficient. A specially constructed tire test-rig is used to experimentally evaluate the performance of the tire sensor and the developed approach. Experimental results show that the proposed tire-road friction coefficient estimation approach is quite promising.

Robust adaptive anti-slip regulation controller for a distributed-drive electric vehicle considering the driver’s intended driving torque

2017 ◽  
Vol 232 (4) ◽  
pp. 562-576 ◽  
Author(s):  
Zhuoping Yu ◽  
Renxie Zhang ◽  
Xiong Lu ◽  
Chi Jin ◽  
Kai Sun
Keyword(s):  
Friction Coefficient ◽  
Electric Vehicle ◽  
State Feedback Control ◽  
Slip Ratio ◽  
The Road ◽  
Road Friction ◽  
Distributed Drive Electric Vehicle ◽  
Robust Adaptive ◽  
Driving Torque ◽  
Road Friction Coefficient

A robust adaptive anti-slip regulation controller which consists of two components, namely a road friction coefficient estimator and a wheel dynamics controller, is designed for distributed-drive electric vehicles. The road friction coefficient estimator is based on the latest non-affine parameter estimation theory to achieve the peak road friction coefficient. Also, working conditions for the road friction coefficient estimator are proposed to avoid the estimation error caused by a small slip ratio. According to the results of the road friction coefficient estimator, the desired reference slip ratio is obtained and the key parameters of the robust adaptive anti-slip regulation controller are modified to make sure that the road conditions can be made full use of. Then, according to the desired reference slip ratio, a state feedback control law with a conditional integrator is designed on the basis of the Lyapunov stability theory for a wheel dynamics controller by analysis of the non-linear characteristics of the tyres and the driver’s intended driving torque and constraints from the ground–tyre adhesion. In addition, it achieves smooth switching between optimal driving and the driver’s intended driving torque rather than normal switching logic. Multi-condition simulations and experiments show that the controller is adaptive to different road conditions, can improve the driving efficiency of the vehicle and can ensure stability of the vehicle. Finally, with comparative experiments, the distributed-drive electric vehicle with a robust adaptive anti-slip regulation controller proves to be more efficient than the traditional vehicle with a traditional anti-slip regulation controller.

scholarly journals Slip Control of Electric Vehicle Based on Tire-Road Friction Coefficient Estimation

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Gaojian Cui ◽  
Jinglei Dou ◽  
Shaosong Li ◽  
Xilu Zhao ◽  
Xiaohui Lu ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Electric Vehicle ◽  
Slip Ratio ◽  
Braking Performance ◽  
Slip Control ◽  
Coefficient Estimation ◽  
Road Friction ◽  
Braking Torque ◽  
Novel Method ◽  
Road Friction Coefficient

The real-time change of tire-road friction coefficient is one of the important factors that influence vehicle safety performance. Besides, the vehicle wheels’ locking up has become an important issue. In order to solve these problems, this paper comes up with a novel slip control of electric vehicle (EV) based on tire-road friction coefficient estimation. First and foremost, a novel method is proposed to estimate the tire-road friction coefficient, and then the reference slip ratio is determined based on the estimation results. Finally, with the reference slip ratio, a slip control based on model predictive control (MPC) is designed to prevent the vehicle wheels from locking up. In this regard, the proposed controller guarantees the optimal braking torque on each wheel by individually controlling the slip ratio of each tire within the stable zone. Theoretical analyses and simulation show that the proposed controller is effective for better braking performance.

Tire–road friction coefficient estimation based on designed braking pressure pulse

2021 ◽  
pp. 095440702098358
Author(s):  
Juqi Hu ◽  
Subhash Rakheja ◽  
Youmin Zhang
Keyword(s):  
Friction Coefficient ◽  
Unscented Kalman Filter ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
Vehicle Speed ◽  
Two Stage ◽  
Slip Ratio ◽  
Road Friction ◽  
Vehicle Motion ◽  
Road Friction Coefficient

Knowledge of tire–road friction coefficient (TRFC) is valuable for autonomous vehicle control and design of active safety systems. This paper investigates TRFC estimation on the basis of longitudinal vehicle dynamics. A two-stage TRFC estimation scheme is proposed that limits the disturbances to the vehicle motion. A sequence of braking pressure pulses is designed in the first stage to identify desired minimal pulse pressure for reliable estimation of TRFC with minimal interference with the vehicle motion. This stage also provides a qualitative estimate of TRFC. In the second stage, tire normal force and slip ratio are directly calculated from the measured signals, a modified force observer based on the wheel rotational dynamics is developed for estimating the tire braking force. A constrained unscented Kalman filter (CUKF) algorithm is subsequently proposed to identify the TRFC for achieving rapid convergence and enhanced estimation accuracy. The effectiveness of the proposed methodology is evaluated through CarSim™-MATLAB/Simulink™ co-simulations considering vehicle motions on high-, medium-, and low-friction roads at different speeds. The results suggest that the proposed two-stage methodology can yield an accurate estimation of the road friction with a relatively lower effect on the vehicle speed.

Experimental Friction and Temperature Investigation on Aircraft Tires

2014 ◽  
Vol 42 (3) ◽  
pp. 116-144 ◽  
Author(s):  
Tim Linke ◽  
Matthias Wangenheim ◽  
Hagen Lind ◽  
Stefan Ripka
Keyword(s):  
Steady State ◽  
Friction Coefficient ◽  
High Speed ◽  
Applied Pressure ◽  
Excitation Frequency ◽  
Infrared Camera ◽  
Slip Angle ◽  
Quasi Steady State ◽  
Test Rig ◽  
Slip Ratio

ABSTRACT For modeling an aircraft tire using the brush model method, the friction coefficient μ between rubber and asphalt should not only be described in terms of the applied pressure and sliding velocity/slip ratio, but also by local temperature inside the contact area. Its influence cannot be neglected, since it leads to significant material property changes. Therefore, investigations on different test rigs are analyzed using thermal recordings of an infrared camera. First measurements are done on a high speed linear tester (HiLiTe), a test rig at the Institute of Dynamics and Vibration Research (IDS) at Leibniz University Hanover, Germany. It allows testing single tread block samples with a constant slip ratio of 100%, that is, pure sliding, on a variety of surfaces such as dry and wet asphalt or concrete, as well as on snow and ice. Results in this paper show that the convection has a smaller impact on tread block cooling than the actual contact between runway surface and sample. Since colder surface temperatures lead to higher friction, this effect antagonizes the excitation frequency, which heats up the rubber sample at high velocities. On long-lasting test sequences a quasi–steady-state friction coefficient might be achieved once these effects start to converge. Still, owing to permanent slip, the abrasion leads to cooling as the hot top layer of the rubber is removed occasionally. In addition to these quasi–steady-state measurements on HiLiTe, the thermal behavior of an aircraft tire is investigated with an autonomously running test rig. It allows realistic testing on an airfield runway by altering load, speed, and slip angle of the tire within and beyond the regions of a passenger aircraft. During the measurements, new and partially unknown effects could be observed. The temperature is mostly influenced by the slip angle followed by speed and load. Furthermore, the contact between tire and runway leads to cooling of the tread but does not affect the temperature inside the grooves. They heat up separately and tend to transfer heat to the tread if the cooling by the runway becomes too low.

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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