自主式轮内电机驱动电动汽车的路径跟踪和横向稳定性综合鲁棒控制

Xianjian Jin, Qikang Wang, Zeyuan Yan, Hang Yang, Guodong Yin
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引用次数: 0

摘要

本文提出了一种集成鲁棒H∞控制策略,通过集成主动前转向(AFS)和直接偏航力矩控制系统(DYC)来提高自主轮内电机驱动电动汽车(AIEV)的路径跟随性能和横向稳定性。首先对 AIEV 系统动力学及其不确定的车辆轨迹跟踪系统进行建模,其中考虑了与轮胎物理极限相关的参数不确定性,并通过规范约束不确定性进行处理,然后开发了具有动态误差的面向控制的车辆轨迹跟踪增强系统。最后设计了 AIEV 轨迹跟随系统的鲁棒 H∞ 控制器(RHCAD),并利用从二次 H∞ 性能和 Lyapunov 稳定性推导出的一组线性矩阵不等式进行求解。同时,减弱了 AIEV 路径跟随系统从外部扰动到受控输出的 H∞ 准则性能指标,并在控制器设计中保证了其他系统要求,如参数不确定性、系统约束等,并利用二次 D 稳定性增强了闭环 AIEV 系统的瞬态响应。通过高保真的 CarSim® 全车模型,对 J 形、单线变道和双线变道操纵进行了仿真,以验证所提控制器的有效性。结果表明,与传统的带 AFS 的线性二次调节器控制器(LQRA)和带 AFS 的鲁棒 H∞ 控制器(RHCA)相比,所提出的集成 AFS 和 DYC 的鲁棒 H∞ 控制策略可以改善 AIEV 的路径跟随性能和横向稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated robust control of path following and lateral stability for autonomous in-wheel-motor-driven electric vehicles
This paper presents an integrated robust H∞ control strategy for improving path following performance and lateral stability of autonomous in-wheel-motor-driven electric vehicles (AIEV) through integration of active front steering (AFS) and direct yaw moment control system (DYC). The AIEV system dynamics and its uncertain vehicle trajectory following system are first modeled, in which parameter uncertainties related to the physical limits of tire are considered and handled via the norm-bounded uncertainties, then the control-oriented vehicle path following augmented system with dynamic errors is developed. The resulting robust H∞ controller with AFS and DYC (RHCAD) of AIEV trajectory-following system is finally designed, and solved utilizing a set of linear matrix inequalities derived from quadratic H∞ performance and Lyapunov stability. Meanwhile, the performance index of H∞ norm from external disturbance to controlled output for AIEV path following is attenuated while other system requirements such as parameter uncertainties, system constraints are also guaranteed in controller design, and then the quadratic D-stability is also utilized to enhance the transient response of the closed-loop AIEV system. Simulations for J-shaped, single lane change and double lane change maneuvers are carried out to verify the effectiveness of the proposed controller with a high-fidelity, CarSim®, full-vehicle model. It can be concluded from the results that the proposed robust H∞ control strategy integrating AFS and DYC can improve the path following performance and lateral stability of AIEV compared with traditional linear quadratic regulator controller with AFS (LQRA) and robust H∞ controller with AFS (RHCA).
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