journal article·2017-06-02Open access

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

Zhen-Feng Wang, Ming-Ming Dong, Liang Gu, Jagat-Jyoti Rath, Ye-Chen Qin, Bin Bai

Applied Sciences· Volume 7· Issue 6

Abstract

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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Research context

OpenAlex topics: Vehicle Dynamics and Control Systems · Soil Mechanics and Vehicle Dynamics · Mechanical Engineering and Vibrations Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China

LAMIH UMR CNRS 8201, University of Valenciennes, 59314 Valenciennes, France

College of Mechanical Engineering & Applied Electronics Technology, Beijing University of Technology, Beijing 100024, China

Funding

the National Natural Science Foundation of China · Innovative Talent Support Program for Post-Doctorate of China · China Postdoctoral Science Foundation

References (27)

Show source-provided references
1. Whitehead, R., Travis, W., Bevly, M.D., and Flowers, G. (2004). A Study of the Effect of Various Vehicle Properties on Rollover Propensity, SAE International. SAE Technical Paper.10.4271/2004-01-2094 ↗
2. Design of a preview controller for vehicle rollover prevention10.1109/TVT.2011.2169687 ↗
3. Yi, K.Y., Yoon, J.Y., and Kim, D.S. (2007, January 9–13). Model-based estimation of vehicle roll state for detection of impending vehicle rollover. Proceedings of the 2007 American Control Conference, New York, NY, USA.10.1109/ACC.2007.4282507 ↗
4. Rajamani, R., Piyabongkan, D., Tsourapas, V., and Lew, J.Y. (2009, January 10–12). Real-time estimation of roll angle and CG hight for active rollover prevention applications. Proceedings of the 2009 American Control Conference, St. Louis, MO, USA.10.1109/ACC.2009.5160045 ↗
5. Parameter and state estimation in vehicle roll dynamics10.1109/TITS.2011.2164246 ↗
6. Differential-Braking-Based rollover prevention for sport utility vehicles with human-in-the-loop evaluations10.1076/vesd.36.4.359.3546 ↗
7. A new predictive lateral load transfer ratio for rollover prevention systems10.1109/TVT.2013.2252930 ↗
8. Rollover risk prediction of heavy vehicle using high-order sliding–mode observer: Experimental results10.1109/TVT.2013.2292998 ↗
9. Slow active suspension control for rollover prevention10.1016/j.jterra.2012.10.001 ↗
10. ISO (1995). Mechanical Vibration-Road Surface Profiles-Reporting of Measured Data, International Organization for Standardization. ISO 8601-1995.
11. Robust design of active suspension system10.1504/IJVD.1993.061831 ↗
12. Model of Road Roughness in Time Domain Based on Rational Function
13. Qin, Y.C., Dong, M.M., Langari, R., Gu, L., and Guan, J.F. (2015). Adaptive hybrid control of vehicle semiactive suspension based on road profile estimation. Shock Vib., 2015.10.1155/2015/636739 ↗
14. Interpolation methods for high-fidelity three-dimensional terrain surfaces10.1016/j.jterra.2010.01.002 ↗
15. Rajamani, R. (2012). Vehicle Dynamics and Control, Springer. [2nd ed.].10.1007/978-1-4614-1433-9 ↗
16. New rollover index for the detection of tripped and untripped rollovers10.1109/TIE.2012.2211312 ↗
17. Pacejia, H.B. (2002). Tyre and Vehicle Dynamics, Butterworth-Heinemann.
18. The influence of the magnetic force generated by the in-wheel motor on the vertical and lateral coupling dynamics of electric vehicles10.1109/TVT.2015.2461635 ↗
19. Output feed-back active suspension control with higher order terminal sliding mode10.1109/TIE.2016.2611587 ↗
20. Rollover index estimation in the presence of sensor faults, unknown inputs, and uncertainties10.1109/TITS.2016.2536683 ↗
21. Non-dimensional design parameters and performance assessment of rainwater harvesting systems10.1016/j.jhydrol.2011.02.009 ↗
22. Qin, Y.C., Dong, M.M., Zhao, F., and Gu, L. (2015, January 15–18). Road profile classification for vehicle semi-active suspension system based on adaptive neuro-fuzzy inference system. Proceedings of the 2015 54th IEEE Conference on Decision and Control, Osaka, Japan.10.1109/CDC.2015.7402428 ↗
23. Suspension system state estimation using adaptive Kalman filtering based on road classification10.1080/00423114.2016.1267374 ↗
24. Qin, Y.C., Xiang, C.L., Wang, Z.F., and Dong, M.M. (2017). Road excitation classification for semi-active suspension system based on system response. J. Vib. Control.10.1177/1077546317693432 ↗
25. Adaptive neural network control for active suspension system with actuator saturation10.1049/iet-cta.2015.1317 ↗
26. Qin, Y.C., Zhao, F., Wang, Z.F., Gu, L., and Dong, M.M. (2017). Comprehensive analysis influence of controllable damper time delay on semi-active suspension control strategies. J. Vib. Acoust.10.1115/1.4035700 ↗
27. A novel tread model for tire modelling using experimental modal parameters10.21595/jve.2016.17336 ↗