分布式电驱动智能车辆轨迹跟踪与横向稳定性控制

Research on trajectory tracking and lateral stability control of distributed electric drive intelligent vehicle

针对智能车辆在高速、低附着等极限工况下轨迹跟踪精度差,易出现侧滑、失稳等危险问题,基于分布式电驱动智能车辆,提出一种分层控制架构的轨迹跟踪算法。基于3自由度单轨车辆动力学模型建立了上层线性时变模型预测控制器(LTVMPC),通过滚动求解带约束的优化问题,得到最优前轮转角,同时由PID纵向驾驶员模型输出期望力矩实现车速跟踪。通过线性二次型调节器(LQR)设计了下层直接横摆力矩控制器,并根据垂直载荷优化分配方法,对计算得到的附加横摆力矩进行了力矩分配。最后,建立Carsim与Matlab/Simulink联合仿真平台,对所建轨迹跟踪控制的有效性进行了仿真分析。仿真结果表明:文中搭建的轨迹跟踪控制策略能显著改善分布式电驱动智能车辆在高速高附着与高速低附着路面的轨迹跟踪精度与横向稳定性。

To address the poor tracking accuracy,the high probability of sideslip and instability of intelligent vehicles in extreme working conditions with high speed and low adhesion,this paper proposes a layered control architecture trajectory tracking algorithm for distributed electric drive intelligent vehicles.Firstly,a Linear Time-Varying Model Predictive Control(LTVMPC)with varying degrees of freedom is built on the three-degree-of-freedom monorail vehicle dynamics model.LTVMPC is employed to solve the constrained optimization problem by rolling to obtain the optimal front wheel angle.In the meantime,the desired torque output of the PID longitudinal driver model is empolyed to achieve vehicle speed tracking.Secondly,a lower direct yaw moment controller is designed through Linear Quadratic Regulator(LQR)and the calculated additional yaw moment is distributedbased on vertical load optimization distribution method.Finally,the co-simulation platform of Carsim and Matlab/Simulink is built,and the effectiveness of the trajectory tracking control is simulated and analyzed.It is shown the trajectory tracking control strategy significantly improves the trajectory tracking accuracy and lateral stability of distributed electric drive intelligent vehicles on both high-speed&high adhesion road surfaces and high-speed&low adhesion ones.