Research on intelligent optimal allocation control strategy for stability and braking of heavy tyre blowout vehicle

汽车工程 电子稳定控制 理论(学习稳定性) 控制(管理) 动态制动 计算机科学 控制理论(社会学) 工程类 缓速器 人工智能 机器学习
作者
Zexuan Han,Yongjie Lu,Haoyu Li,Junning Zhang
出处
期刊:Proceedings Of The Institution Of Mechanical Engineers, Part K: Journal Of Multi-body Dynamics [SAGE Publishing]
卷期号:238 (4): 524-538
标识
DOI:10.1177/14644193241286685
摘要

The traditional control strategy mainly compensates and corrects the driving state of heavy vehicles with a tyre blowout, and rarely considers the need for emergency braking. It is also difficult to effectively coordinate the problems of lateral yaw, slip and tailspin, and longitudinal braking performance degradation. For this, an intelligent optimization allocation control strategy combining stability control and braking control is innovatively designed in this article. The joint simulation model for heavy tyre blowout vehicles is built based on the Dugoff tyre blowout model and the TruckSim vehicle model. A linear quadratic form regulator stable control based on the particle swarm optimization algorithm optimization is used to dynamic equilibrium of the additional yaw moment generated by the vehicle tyre blowout. A logic threshold braking control based on adaptive adjustment is adopted to achieve an ideal braking effect for the vehicle. In order to simultaneously consider the stability and braking performance of vehicles with blowout tyre, a braking force distribution strategy and a fuzzy optimization allocation algorithm are proposed to achieve coordination of lateral and longitudinal control strategies. The results indicate that intelligent optimized allocation control can effectively correct the deviation trajectory of a heavy tyre blowout vehicle, enabling it to achieve rapid braking while maintaining stability.
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