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 引用本文: 汪洪波, 王春阳, 高含, 徐世寒. 基于FFUKF路面附着系数估计的汽车牵引力控制. 力学学报, 2022, 54(7): 1866-1879.
Wang Hongbo, Wang Chunyang, Gao Han, Xu Shihan. Vehicle traction force control based on the road adhesion coefficient estimation by FFUKF. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(7): 1866-1879.
 Citation: Wang Hongbo, Wang Chunyang, Gao Han, Xu Shihan. Vehicle traction force control based on the road adhesion coefficient estimation by FFUKF. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(7): 1866-1879.

## VEHICLE TRACTION FORCE CONTROL BASED ON THE ROAD ADHESION COEFFICIENT ESTIMATION BY FFUKF

• 摘要: 以后驱牵引车为研究对象, 设计了基于路面附着系数估计的牵引力控制系统(TCS). 在路面附着系数估计方面, 针对传统卡尔曼滤波难以跟踪时变非线性系统的问题, 本文将模糊控制理论和衰减记忆滤波思想引入无迹卡尔曼滤波, 设计一种基于模糊遗忘因子的无迹卡尔曼滤波路面附着系数估计方法, 提高了算法的跟踪性能. 牵引力控制包括扭矩控制和制动控制. 在TCS扭矩控制方面, 分别利用路面附着系数和驱动轮滑转率在目标滑转率附近时的车辆加速度计算目标基础扭矩, 根据车辆行驶状态和抖振度参量, 基于可拓控制理论划分经典域、可拓域和非域, 通过可拓集的关联函数得到动态权重系数, 将上述两种方法计算得到的目标基础扭矩进行可拓融合设计出基础扭矩. 之后, 以实际滑转率和目标滑转率之间的误差作为输入, 采用模糊自整定PI控制器得到目标反馈扭矩. 在制动控制方面, 针对两种典型路面分别设计了PI控制压力和附着差压力. 实车试验结果表明, 基于模糊遗忘因子的无迹卡尔曼滤波算法能够更加快速地跟踪路面附着系数的变化, 同时基于路面附着系数估计的TCS控制策略能够有效抑制驱动轮过度滑转, 将驱动轮滑转率控制在最佳范围内, 显著提高了车辆的动力性.

Abstract: Traction control system (TCS) based on road adhesion coefficient estimation is designed for the rear drive tractor. Firstly , to track the time-varying nonlinear system in the classical Kalman filter, a fuzzy control theory and an attenuated memory filter are introduced into untraced Kalman filter, and the fuzzy forgetting factor unscented Kalman filter (FFUKF) is proposed to estimate road adhesion coefficient, so as to improve the tracking performance of the algorithm. Traction control includes torque control and braking control. Then, for the TCS torque control, the road adhesion coefficient and the vehicle acceleration when the slip rate of the driving wheel is near the target slip rate are used to calculate the target base torque, respectively. According to the vehicle state and chattering parameters, the extension set is divided into the classical domain, extension domain and non-domain with the extension control theory, and the dynamic weight coefficient is obtained by the correlation function of extension set. The base torque is designed by extension fusion of the target base torques calculated by the above methods. Next, the error between the actual slip rate and the target slip rate is used as the input, and the target feedback torque is obtained by using the fuzzy self-tuning PI controller. In terms of braking control, the PI pressure control and adhesion difference pressure are designed on two typical road surfaces, respectively. Finally, the test results show that the proposed FFUKF algorithm can track the tire-road friction coefficient more quickly, and the proposed TCS control strategy can effectively restrain the excessive slip of the driving wheels to control the slip rate of drive wheel in the best range, so that improving vehicle dynamic performance significantly.

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