A Novel Rollover Warning Approach for Commercial Vehicles Using Unscented Kalman Filter

Junjian Hou,Heyang Feng,Haizhu Lei,Zihao Li,Yuming Yin,Zhijun Fu,Minghui Cui,Peixin Yuan,Mingxu Zhang,Yuqing Xu,Xianjian Jin

doi:10.1155/2022/7503715

Abstract

Roll responses of the semitrailer and the tractor provide higher lead time and characterise the roll instability of the commercial vehicles subjected to directional manoeuvres at highway speeds. This paper proposes a novel rollover index based on the synthesized roll angles of the tractor and trailer. Owing to the poor measurability, the unscented Kalman filter (UKF) algorithm is used to estimate the roll angle of the track and trailer, respectively. Meanwhile, different weight coefficients are considered in the rollover index to eliminate the influence of mutual coupling between the tractor and the trailer and improve the accuracy of the warning. For the practical implementation of the algorithm, a two-stage rollover warning method triggered by the video and audio is finally proposed to reduce the possibilities of false warnings. Co-simulation is presented to prove the validity of the proposed rollover warning approach.

Highlights

In heavy-duty semitrailer vehicles, owing to their heavy load, long vehicle body length, and high mass center (CG), the stability is worse compared with other vehicles
E semitrailer rollover index can be roughly divided into two categories: static rollover index and dynamic rollover index. e static index mainly refers to the static stability coefficient (SSF) [6], which is defined as the ratio between the width of the half-track and the height of the center of gravity
Dynamic rollover index is derived by considering the roll responses of different units of an articulated vehicle under dynamic manoeuvre and has been proved to be more reliable compared with the static index

Summary

Introduction

In heavy-duty semitrailer vehicles, owing to their heavy load, long vehicle body length, and high mass center (CG), the stability is worse compared with other vehicles. E NRSSM index, based on roll responses of the semitrailer sprung mass and the tractor front and rear axles, is considered to be a more reliable rollover metric that may yield reasonably good performance with respect to the sensitivity, reliability, and lead time. Is study proposes a novel online rollover index based on the composite roll angles of the tractor and the trailer of semitrailer commercial vehicles. E notable contributions of the study include (i) the synthesis of an rollover index based on the roll angles of the tractor and trailer to achieve higher accuracy and reliability, (ii) an UKF algorithm is used to estimate the roll angles of the tractor and trailer to enhance the measurability, and (iii) design of the two-stage warning method that relies only on roll response of the commercial vehicles and triggered by video and audio, which generally reduce the possibilities of false warnings.

Vehicle Dynamics Model

Rollover Index Design

Unscented Kalman Filter Estimate Algorithm

Simulation and Implementation Discussion