A novel tread model for tire modelling using experimental modal parameters

Wang, Zhenfeng; Dong, Ming; Zhao, Weipeng; Li, Gu

doi:10.21595/jve.2016.17336

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…Assuming c p1 = c p2 = c p and k s1 = k s2 = k s , and substituting Equations (28) and (29) into Equation (27), overall equations of motion are obtained as follows. …”

Section: -Dof Roll Dynamics Modelmentioning

confidence: 99%

“…It can be seen from the results that vehicle response for different dynamics models have significant impact on roll behavior under level ISO-C road excitation, and influence of road excitation cannot be ignored in this situation [21][22][23][24][25][26][27]. To further illustrate difference between 6-DOF and 9-DOF models with road excitation and various steering wheel inputs, vehicle responses were statistically analyzed.…”

Section: Case 2: Level Iso-c Road Excitationmentioning

confidence: 99%

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Influence of Road Excitation and Steering Wheel Input on Vehicle System Dynamic Responses

Wang

Dong

et al. 2017

Applied Sciences

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Considering the importance of increasing driving safety, the study of safety is a popular and critical topic of research in the vehicle industry. Vehicle roll behavior with sudden steering input is a main source of untripped rollover. However, previous research has seldom considered road excitation and its coupled effect on vehicle lateral response when focusing on lateral and vertical dynamics. To address this issue, a novel method was used to evaluate effects of varying road level and steering wheel input on vehicle roll behavior. Then, a 9 degree of freedom (9-DOF) full-car roll nonlinear model including vertical and lateral dynamics was developed to study vehicle roll dynamics with or without of road excitation. Based on a 6-DOF half-car roll model and 9-DOF full-car nonlinear model, relationship between three-dimensional (3-D) road excitation and various steering wheel inputs on vehicle roll performance was studied. Finally, an E-Class (SUV) level car model in CARSIM ® was used, as a benchmark, with and without road input conditions. Both half-car and full-car models were analyzed under steering wheel inputs of 5 • , 10 • and 15 • . Simulation results showed that the half-car model considering road input was found to have a maximum accuracy of 65%. Whereas, the full-car model had a minimum accuracy of 85%, which was significantly higher compared to the half-car model under the same scenario.

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“…Assuming c p1 = c p2 = c p and k s1 = k s2 = k s , and substituting Equations (28) and (29) into Equation (27), overall equations of motion are obtained as follows. …”

Section: -Dof Roll Dynamics Modelmentioning

confidence: 99%

Section: Case 2: Level Iso-c Road Excitationmentioning

confidence: 99%

Influence of Road Excitation and Steering Wheel Input on Vehicle System Dynamic Responses

Wang

Dong

et al. 2017

Applied Sciences

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Train wheel tread defects detection based on image registration

Zhou

Wei

2017

2017 IEEE International Conference on Imaging Systems and Techniques (IST)

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Road profile estimation for suspension system based on the minimum model error criterion combined with a Kalman filter

Wang¹,

Dong²,

Qin³

et al. 2017

J. vibroeng.

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This paper presents a novel approach for improving the estimation accuracy of the road profile for a vehicle suspension system. To meet the requirements of road profile estimation for road management and reproduction of system excitation, previous studies can be divided into data-driven and model based approaches. These studies mainly focused on road profile estimation while seldom considering the uncertainty of parameters. However, uncertainty is unavoidable for various aspects of suspension system, e.g., varying sprung mass, damper and tire nonlinear performance. In this study, to improve the estimation accuracy for a varying sprung mass, a novel algorithm was derived based on the Minimum Model Error (MME) criterion and a Kalman Filter (KF). Since the MME criterion method utilizes the minimum value principle to solve the model error based on a model error function, the MME criterion can effectively deal with the estimation error. Then, the proposed algorithm was applied to a 2 degree-of-freedom (DOF) suspension system model under ISO Level-B, ISO Level-C and ISO Level-D road excitations. Simulation results and experimental data obtained using a quarter-vehicle test rig revealed that the proposed approach achieves higher road estimation accuracy compared to traditional KF methods.

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A novel tread model for tire modelling using experimental modal parameters

Cited by 5 publications

References 14 publications

Influence of Road Excitation and Steering Wheel Input on Vehicle System Dynamic Responses

Influence of Road Excitation and Steering Wheel Input on Vehicle System Dynamic Responses

Train wheel tread defects detection based on image registration

Road profile estimation for suspension system based on the minimum model error criterion combined with a Kalman filter

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