基于AFS和DYC集成控制的分布式驱动电动汽车横摆稳定性控制

为提高分布式驱动电动汽车行驶稳定性,基于模型预测控制提出一种将驱动电机和各执行器的饱和输出力矩作为控制输入约束、将横摆角速度作为输出约束的汽车稳定性控制方法。建立2自由度的车辆状态空间模型作为预测模型,计算跟踪期望横摆角速度所需的附加横摆力矩,考虑电机和液压制动系统等约束设计三种控制分配算法,将上述算法应用于四轮驱动的7自由度整车模型进行仿真,结果表明:以轮胎负荷率平方的方差与均值加权最小为目标的优化控制分配方法,可有效提高分布式驱动电动汽车的横摆稳定性。

Yaw stability control for distributed drive electric vehicle based on AFS and DYC integrated control

To improve the driving stability of distributed drive electric vehicles, a model stability control method is proposed based on model predictive control, which uses the saturated output torque of the drive motor and actuators as control input constraints and yaw rate as output constraints. Establish a 2-DOF vehicle state space model as a prediction model, calculate the additional yaw moment required to track the expected yaw angular velocity, and consider the constraints of the motor and hydraulic brake system to design three control allocation algorithms, The above mentioned algorithm is applied to a four-wheel-drive 7-DOF vehicle model for simulation. The results show that the optimal control allocation method with the minimum variance of the square of the tire load rate and the weighted mean value as the goal can effectively improve the stability of the distributed drive electric vehicle.