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

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.

[1]  Rajesh Rajamani,et al.  A New Predictive Lateral Load Transfer Ratio for Rollover Prevention Systems , 2013, IEEE Transactions on Vehicular Technology.

[2]  Luca G. Lanza,et al.  Non-dimensional design parameters and performance assessment of rainwater harvesting systems , 2011 .

[3]  Liang Gu,et al.  Suspension system state estimation using adaptive Kalman filtering based on road classification , 2017 .

[4]  Michael Defoort,et al.  Rollover Index Estimation in the Presence of Sensor Faults, Unknown Inputs, and Uncertainties , 2016, IEEE Transactions on Intelligent Transportation Systems.

[5]  Abdelaziz Benallegue,et al.  Rollover Risk Prediction of Heavy Vehicle Using High-Order Sliding-Mode Observer: Experimental Results , 2014, IEEE Transactions on Vehicular Technology.

[6]  Rajesh Rajamani,et al.  New Rollover Index for the Detection of Tripped and Untripped Rollovers , 2013, IEEE Transactions on Industrial Electronics.

[7]  P. S. Els,et al.  Slow active suspension control for rollover prevention , 2013 .

[8]  Seongjin Yim,et al.  Design of a Preview Controller for Vehicle Rollover Prevention , 2011, IEEE Transactions on Vehicular Technology.

[9]  Shuzhi Sam Ge,et al.  Adaptive neural network control for active suspension system with actuator saturation , 2016 .

[10]  Hamid Reza Karimi,et al.  Output Feedback Active Suspension Control With Higher Order Terminal Sliding Mode , 2017, IEEE Transactions on Industrial Electronics.

[11]  Rajesh Rajamani,et al.  Parameter and State Estimation in Vehicle Roll Dynamics , 2011, IEEE Transactions on Intelligent Transportation Systems.

[12]  Mingming Dong,et al.  Road excitation classification for semi-active suspension system based on system response , 2018 .

[13]  Liang Gu,et al.  Adaptive Hybrid Control of Vehicle Semiactive Suspension Based on Road Profile Estimation , 2015 .

[14]  John B. Ferris,et al.  Interpolation methods for high-fidelity three-dimensional terrain surfaces , 2010 .

[15]  József Bokor,et al.  Robust design of active suspension system , 2014 .

[16]  Liang Gu,et al.  Comprehensive Analysis for Influence of Controllable Damper Time Delay on Semi-Active Suspension Control Strategies , 2017 .

[17]  Liang Gu,et al.  A novel tread model for tire modelling using experimental modal parameters , 2017 .

[18]  Huei Peng,et al.  Differential-Braking-Based Rollover Prevention for Sport Utility Vehicles with Human-in-the-loop Evaluations , 2001 .

[19]  Chao Lu,et al.  The Influence of the Magnetic Force Generated by the In-Wheel Motor on the Vertical and Lateral Coupling Dynamics of Electric Vehicles , 2016, IEEE Transactions on Vehicular Technology.