Shi Xuanyu, Wang Hai, Cai Yingfeng, Sun Xiaoqiang, Chen Long, Yang Chao
School of Automotive and Traffic Engineering of Jiangsu University, Zhenjiang 212013, China.
Automotive Engineering Research Institute of Jiangsu University, Zhenjiang 212013, China.
ISA Trans. 2024 Oct;153:404-419. doi: 10.1016/j.isatra.2024.07.022. Epub 2024 Jul 27.
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.
在高速转弯时，商用车会经历显著的侧偏角和轮胎力饱和，这可能导致严重的交通事故。引入智能驾驶技术来开发一种超越稳定性约束并使车辆保持漂移状态的可控方案，对于提高驾驶安全性至关重要。因此，基于分布式驱动三轴（DDTA）商用车的模型特性，提出了一种两阶段辅助漂移控制器。在辅助漂移阶段，采用时变模型预测控制（MPC）来跟踪期望状态，并在极端工作条件下实现稳态漂移路径跟踪。基于道路信息实施两阶段控制器切换策略。在横摆稳定性控制阶段，一个先进的辅助系统促进协同控制，以平稳地恢复轮胎附着和车辆横摆。仿真结果表明，即使中后轴附着力饱和且车辆峰值侧偏角达到32.09°时，该控制策略也能确保一致的路径跟踪性能。完成漂移后，车辆横摆成功恢复到稳定状态。随后，小型车辆测试通过阐明转向和分布式驱动车辆的瞬态不稳定演变，对相关结论进行了定性分析。从而扩展了车辆的可控稳定性边界，提高了漂移技术的工程可行性。
