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基于UKF车辆状态及路面 附着系数估计的AFS控制
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AFS Control Based on Estimation of Vehicle State and Road Coefficient Using UKF Method
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    摘要:

    本文侧重于主动前轮转向(Active Front Steering,AFS)控制系统的应用性与可行性研究,针对紧急转向工况下轮胎呈现强非线性问题,以及AFS控制算法中部分状态量难以获取、路面附着系数对车辆稳定性有重要影响但难以直接测量等问题,设计非线性滑模控制器以综合考虑载荷转移、轮胎非线性及路面条件等对操稳性影响,同时,通过ESP系统现有的IMU传感器测量信息,运用无迹卡尔曼滤波(Unscented Kalman Filter,UKF)算法为滑模控制器动态估计车辆状态信息和路面附着系数.在得到期望轮胎侧偏力后,通过非线性轮胎模型精确反求所需叠加转角,以在“轮胎-路面”附着能力范围内检验控制系统的有效性.最后,高附着系数情况下的鱼钩测试仿真及低附着系数时的角阶跃转向仿真共同表明,通过IMU与UKF结合的状态估计确保了AFS控制系统的可行性,有效提高了车辆操纵稳定性.

    Abstract:

    This paper mainly focuses on the application and feasibility of the Active Front Steering (AFS) control system. Considering that tire behaves nonlinearly during emergency steering and that the vehicle states involved in the AFS control system and the road adhesion coefficient having important effect on the stability are difficult to measure, a controller using nonlinear sliding mode algorithm was designed to synthetically take into account the influence of load transfer, tire nonlinearity, and road on the vehicle stability. Meanwhile, with the use of signals measured from the existing Inertial Measurement Unit (IMU) sensor of ESP system and the application of Unscented Kalman Filter (UKF) algorithm, a state estimator was established to dynamically estimate the vehicle state information and road adhesion coefficient for sliding mode controller. On the above basis, the desired superposition angle is precisely reversely calculated by the nonlinear tire model after the desired tire force is obtained, which verifies the effectiveness of the control system over the "tire-road" attachment capability range. Finally, simulations of fishhook test with high road adhesion and step input with low road adhesion indicate that the state estimation combined with IMU and UKF ensures the feasibility of AFS control system and effectively improves the vehicle stability.

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周兵,邱香 ,吴晓建,龙乐飞.基于UKF车辆状态及路面 附着系数估计的AFS控制[J].湖南大学学报:自然科学版,2019,46(8):1~9

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  • 在线发布日期: 2019-09-02
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