Test for Tire Quasi-Static Longitudinal Force vs. Longitudinal Displacement and Quasi-Static Lateral Force vs. Lateral Displacement

The necessity and importance of studying the dynamical characteristics of ramp steering was described. After the force analysis of ramping going up, down and along the slope, Especially don‘t ignored unchanged load distribution that was caused by the longitudinal force and lateral force, Establish the mathematical model of traction and braking force. Through the simulation experiment, the result showed that the traction and braking force changed with definite rules when the tracked vehicle turned on the slope, which has practical significance for the further study of the vehicle’s power matching problems.

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Pavement State Recognition Method Considering Slope

Journal of Physics Conference Series ◽

10.1088/1742-6596/2113/1/012080 ◽

2021 ◽

Vol 2113 (1) ◽

pp. 012080

Author(s):

Xiuhao Xi ◽

Jun Xiao ◽

Qiang Zhang ◽

Yanchao Wang

Keyword(s):

Surface Condition ◽

Lateral Force ◽

Longitudinal Force ◽

Operating Conditions ◽

Road Surface ◽

Tire Model ◽

State Recognition ◽

Adhesion Coefficient ◽

The Road ◽

Real Time Tracking

Abstract For the problem of road surface condition recognition, this paper proposes a real-time tracking method to estimate road surface slope and adhesion coefficient. Based on the fusion of dynamics and kinematics, the current road slope of the vehicle which correct vertical load is estimated. The effect of the noise from dynamic and kinematic methods on the estimation results is removed by designing a filter. The normalized longitudinal force and lateral force are calculated by Dugoff tire model, and the Jacobian matrix of the vector function of the process equation is obtained by combining the relevant theory of EKF algorithm. The road adhesion coefficient is estimated finally. The effectiveness of the algorithm is demonstrated by analyzing the results under different operating conditions, such as docking road and bisectional road, using a joint simulation of Matlab/Simulink and Carsim.

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Adhesion state estimation based on improved tire brush model

Advances in Mechanical Engineering ◽

10.1177/1687814017747706 ◽

2018 ◽

Vol 10 (1) ◽

pp. 168781401774770

Author(s):

Bei Shaoyi ◽

Li Bo ◽

Zhu Yanyan

Keyword(s):

Lateral Force ◽

Longitudinal Force ◽

Lateral Acceleration ◽

Stable Range ◽

The Road ◽

Nonlinear Compensation ◽

The Stability ◽

Standard Calculation ◽

Double Nonlinear ◽

Brush Model

On the basis of calculating the longitudinal force using the original brush model, we simplify the tire structure and consider the lateral force generated by the lateral elasticity of the tread. At the same time, the boundary conditions between the adhesion area and the slip zone in the contact area of the tire are fully discussed. By establishing an improved tire brush model, the error caused by neglecting the sideslip characteristics is avoided, and the adaptability of the tire model is improved. A double nonlinear compensation method based on the lateral acceleration deviation and the yaw rate deviation is employed to estimate the road adhesion coefficient, which is closer to the actual attachment situation than the standard calculation. Based on this model, the vehicle stability coefficient k is defined and calculated to describe the stability of the vehicle during the driving process. The modeling results show that the value of k is always in the stable range of [0, 1]. Therefore, the vehicle that utilizes the improved tire brush model is always within the controllable range in the driving process, which verifies the effectiveness of the model.

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RANS-BASED CFD PREDICTION OF THE HYDRODYNAMIC COEFFICIENTS OF DARPA SUBOFF GEOMETRY IN STRAIGHT-LINE AND ROTATING ARM MANOEUVRES

The International Journal of Maritime Engineering ◽

10.5750/ijme.v157ia1.947 ◽

2021 ◽

Vol 157 (A1) ◽

Author(s):

Z Q Leong ◽

D Ranmuthugala ◽

I Penesis ◽

H D Nguyen

Keyword(s):

Computational Cost ◽

Turbulence Models ◽

Lateral Force ◽

Longitudinal Force ◽

Independent Effect ◽

Analysis Tool ◽

Hydrodynamic Coefficients ◽

Cfd Simulations ◽

Fine Mesh ◽

Straight Line

Computational Fluid Dynamics (CFD) simulations using Reynolds Averaged Navier-Stokes (RANS) equations are increasingly adopted as an analysis tool to predict the hydrodynamic coefficients of underwater vehicles. These simulations have shown to offer both a high degree of accuracy comparable to experimental methods and a greatly reduced computational cost compared to Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS). However, one of the major challenges faced with CFD simulations is that the results can vary greatly depending on the numerical model settings. This paper uses the DARPA SUBOFF hull form undergoing straight-line and rotating arm manoeuvres at different drift angles to analyse the hydrodynamic forces and moments on the vehicle against experimental data, showing that the selection of the boundary conditions and turbulence models, and the quality of the mesh model can have a considerable and independent effect on the computational results. Comparison between the Baseline Reynolds Stress Model (BSLRSM) and Shear Stress Transport with Curvature Correction (SSTCC) were carried out for both manoeuvres, showing that with a sufficiently fine mesh, appropriate mesh treatment, and simulation conditions matching the experiments; the BSLRSM predictions offer good agreement with experimental measurements, while the SSTCC predictions are agreeable with the longitudinal force but fall outside the experimental uncertainty for both the lateral force and yawing moment.

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Simultaneous Optimal Distribution of Lateral and Longitudinal Tire Forces for the Model Following Control

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.1850533 ◽

2004 ◽

Vol 126 (4) ◽

pp. 753-763 ◽

Cited By ~ 157

Author(s):

Ossama Mokhiamar ◽

Masato Abe

Keyword(s):

Lateral Force ◽

Longitudinal Force ◽

Equality Constraints ◽

Steering Wheel ◽

Slip Angle ◽

Force Distribution ◽

Distribution Method ◽

Tire Force ◽

Model Following Control ◽

Tire Forces

This paper presents a proposed optimum tire force distribution method in order to optimize tire usage and find out how the tires should share longitudinal and lateral forces to achieve a target vehicle response under the assumption that all four wheels can be independently steered, driven, and braked. The inputs to the optimization process are the driver’s commands (steering wheel angle, accelerator pedal pressure, and foot brake pressure), while the outputs are lateral and longitudinal forces on all four wheels. Lateral and longitudinal tire forces cannot be chosen arbitrarily, they have to satisfy certain specified equality constraints. The equality constraints are related to the required total longitudinal force, total lateral force, and total yaw moment. The total lateral force and total moment required are introduced using the model responses of side-slip angle and yaw rate while the total longitudinal force is computed according to driver’s command (traction or braking). A computer simulation of a closed-loop driver-vehicle system subjected to evasive lane change with braking is used to prove the significant effects of the proposed optimal tire force distribution method on improving the limit handling performance. The robustness of the vehicle motion with the proposed control against the coefficient of friction variation as well as the effect of steering wheel angle amplitude is discussed.

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Experimental Device of Drilling String Dynamics in Horizontal Well and its Application

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.683.690 ◽

2013 ◽

Vol 683 ◽

pp. 690-693 ◽

Cited By ~ 1

Author(s):

Dong Dong Shao ◽

Zhi Chuan Guan ◽

Xin Wen

Keyword(s):

Horizontal Well ◽

Lateral Displacement ◽

Lateral Force ◽

Experimental Results ◽

Experimental Device ◽

Simulated Experiment ◽

Bottom Hole ◽

Drilling String ◽

Rotary Speed ◽

Set Up

According to the principle of similitude, a simulation experimental device for investigating drilling string dynamics in horizontal well was designed and set up. The rotary speed, WOB, drilling string lateral displacement, bottom hole WOB fluctuations and lateral force of the bit, etc. can be measured under different WOB and rotary speed by the experimental device; Some debugging experiments have been done by means of the device under different weights on bit and rotary speeds. The simulated experiment has many advantages comparing to the actual experiment, such as less operators, less times and moneys. It is easy to operate, the drilling string movement can be visually observed and all of the experimental results can be used to the actual drilling.

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A Novel Dynamic Data Driven Tire Model

10.21203/rs.3.rs-724346/v1 ◽

2021 ◽

Author(s):

Junning Zhang ◽

Shaopu YANG ◽

Yongjie LU

Keyword(s):

Experimental Data ◽

Knowledge Base ◽

Vehicle Dynamics ◽

Mechanical Characteristics ◽

Slip Rate ◽

Lateral Force ◽

Longitudinal Force ◽

Dynamics Simulation ◽

Slip Angle ◽

Tire Model

Abstract In the study of vehicle dynamics, the accurate description of tire mechanical characteristics is the basis and key of vehicle dynamics simulation. An innovative tire model is proposed based on fuzzy algorithm and a sinusoidal membership function is used to design fuzzy rules. In order to ensure the accuracy of tire behavior calculation, this model is driven by a small amount of experimental data of tire mechanical characteristics. This tire model consists of four layers of fuzzy systems, each of which has a knowledge base. The data in knowledge base I is obtained by experiments, and the data of knowledge base II is computed by the upper system, and so is the later system. Then, the input signal, the change rate of side slip angle and slip rate, is considered to improve the calculation accuracy of the model. The proposed fuzzy tire model can accurately predict the longitudinal force, lateral force and self-aligning torque of the tire under unknown conditions. Finally, by comparing the fuzzy tire model with the experimental data, it is found that the maximum RRMSE (Relative Root Mean Square Error) value is not more than 0.14. It is proved that the model can accurately describe the tire mechanical characteristics under combined conditions.

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