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

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.

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

“…Also, the ISO level-B, ISO Level-C and ISO Level-D were calculated and used as the road excitation [29]. Note that it was assumed the tire did not lose contact with the ground [36][37][38][39][40].…”

Analysis of explicit model predictive control for path-following control

“…In the future works, we aim to design an explicit MPC controller for path-following control where a vehicle model considers road profile excitation. For example, a vehicle model can be combined with a three-dimensional (3-D) road profile excitation, which has been presented in [ 29 ]. One of the main contributions of this paper is to prove the performance of explicit MPC controllers, which can reduce the computational complexity of MPC so that the MPC scheme can be applied for relatively faster and/or smaller problems.…”

Using Real-Time Dynamic Prediction to Implement IoV-Based Collision Avoidance

“…In this section, we will be introducing our predictive method. The main idea comes from vehicle dynamics [17][18][19]: the movement of a vehicle will not be a large value within a short time interval, such as the heading angle and the absolute position. Hence, if a video has a high resolution and FPS, we can estimate whether it is a reasonable position or not by calculating the difference between the two positions and using some skill of vehicle dynamics on the time axis to get the future confidence region.…”