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

Author:

Hou Junjian1,Lei Haizhu1,Fu Zhijun1ORCID,Yuan Peixin1,Yin Yuming2ORCID,Feng Heyang1,Li Zihao1,Zhang Mingxu1,Cui Minghui1,Xu Yuqing1

Affiliation:

1. Henan Provincial Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou, China

2. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, China

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.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Reference23 articles.

1. A review of anti-rollover prediction and control technologies for heavy-duty vehicles;Y. He;Journal of Transport Information and Safety,2019

2. Dynamic Rollover Prediction of Heavy Vehicles Considering Critical Frequency

3. Active steering control for vehicle rollover risk reduction based on slip angle estimation

4. Robust active steering control for vehicle rollover prevention

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