State observation of nonlinear off-road vehicle system under complex maneuver condition

Abstract

The information of vehicle attitude and tire force under complex environment and maneuver condition is of great significance for system risk prediction and active control system intervention. In order to collect the accurate system states, the coupling vehicle dynamics model and moving horizon estimation method are employed to solve the online optimization problem based on the premise of rolling optimization. Furthermore, the accurate observation and acquisition of the vehicle system state are realized. On this basis, the simulation process of the vehicle state observation using moving horizon estimation method and unscented Kalman filter algorithm are implemented, respectively. The corresponding observation results under complex maneuvering conditions are further validated by using the hardware-in-the-loop experimental platform. Finally, the comparison of the observation results obtained by the unscented Kalman filter and moving horizon estimation algorithms demonstrate that the moving horizon estimation method can effectively improve the observation accuracy of vehicle system state in complex environment, including vehicle roll angle and tire dynamic force. The results obtained through moving horizon estimation method are conducive to the further signal early warning, risk prediction and assessment, as well as systematic intervention and active rollover control.

Training Evaluation Model of Outdoor Cross-Country Sports Tourism Project Based on Lagrangian Differential Equation Calculation

“…The primary frequency is lower than the analog value. In this paper, the experimental data and simulation data are used to obtain two different reaction indices [7]. The purpose is to test whether the simulation mode can better reflect the vibration response of the human body when running.…”

Anti-Overturning Capability and Fuzzy PID Speed Control for Four-Way Shuttle Vehicles in Processed Grain Storage

“…Zhao J Z, et al [15] designed an anti-overturning system for vehicles with a dynamic simulation model and analyzed the control performance of the system under different conditions. Gao Z, et al [16] adopted the coupled vehicle dynamics model and the moving horizon estimation method for online optimization, and realized the accurate observation and acquisition of the vehicle system state. Li B, et al [17] established a comprehensive model of vehicle dynamics and analyzed the stability of vehicles on the yaw plane under different working conditions.…”

A hybrid sliding mode controller design for vibration suppression in a hydraulic suspension system with vertical load disturbance

“…The hydraulic suspension system is vital to ensure riding comfort in off-road vehicles by exerting lifting force and implementing active damping control. This is particularly important, when a vehicle operates under random disturbance conditions in which road excitation fluctuation can lead to dynamic instability (Gao et al, 2020; Taghavifar, 2020; Yoon et al, 2021). The dynamic model and tracking regulator are important components for obtaining appropriate control performance (Gong et al, 2019; Taghavifar et al, 2019; Wang et al, 2021).…”