基于模型预测控制的滑移率控制方法

Slip rate control method based on model predictive control

为了解决汽车控制中的安全问题,提高四轮轮毂电动汽车紧急制动时的纵向稳定性,本文提出一种基于模型预测控制的滑移率控制方法。首先,基于扩展卡尔曼滤波的车辆纵向速度估计器对车辆纵向速度进行准确估计,再利用基于限定记忆的递推最小二乘法辨识得到紧急制动工况下车辆的最佳滑移率。其次,上层模型预测控制器跟踪最佳滑移率,在满足安全约束条件下优化求解前后轮在不同路面附着条件下所需的制动力矩,下层转矩分配控制器在电机转矩和电池荷电状态约束条件下分配液压和再生制动力矩,提高能量回收效率。最后,在不同工况下进行仿真实验,实验结果表明本文控制系统能保证紧急制动过程中车辆的安全性和可靠性。

In automotive electronic controls,safety issues are always of paramount importance.Therefore,this paper proposes a slip rate control method based on MPC to improve the longitudinal stability of fourwheel-wheel electric vehicles during emergency braking.Firstly,the vehicle longitudinal velocity estimator based on extended Kalman filter accurately estimates the longitudinal speed of the vehicle,and then the recursive least squares method based on limited memory is used to identify the optimal slip rate of the vehicle under the emergency braking condition.Secondly,the upper model predicts that the controller tracks the optimal slip rate,optimizes the braking torque required by the front and rear wheels under different road surface attachment conditions to meet the safety constraints,and the lower torque distribution controller distributes hydraulic and regenerative braking torque under the constraints of battery state of charge to improve the energy recovery efficiency.Finally,simulation experiments are carried out under different working conditions and it is shown that the proposed control system can ensure the safety and reliability of the emergency braking process.