Xuanyu Shi , Hai Wang , Yingfeng Cai , Xiaoqiang Sun , Long Chen , Chao Yang
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引用次数: 0
Abstract
When maneuvering corners at high speeds, commercial vehicles experience significant sideslip angles and tire force saturation, which can lead to severe traffic accidents. Incorporating intelligent driving technology to develop a controllable scheme that surpasses stability constraints and maintains the vehicle in a drift state is crucial for enhancing driving safety. Therefore, based on the model characteristics of distributed drive three-axle(DDTA) commercial vehicles, a two-stage auxiliary drift controller is proposed. In the auxiliary drift stage, time-varying model predictive control (MPC) is employed to track the desired states and achieve steady-state drift path tracking under extreme working conditions. A two-stage controller switching strategy is implemented based on road information. In the yaw stability control stage, an advanced auxiliary system facilitates cooperative control to smoothly restore tire attachment and vehicle yaw. Simulation results demonstrate that the control strategy ensures consistent path tracking performance even when adhesion of the middle and rear axle saturates and peak vehicle sideslip angle reaches 32.09°. After completing the drifting, vehicle yaw successfully returns to a stable state. Subsequently, miniaturized vehicle tests qualitatively analyze relevant conclusions by elucidating transient instability evolution in vehicles subjected to steering and distributed drive. The controllable stability boundary of the vehicle is thus expanded, thereby enhancing the engineering feasibility of drift technology.
期刊介绍:
ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.