In order to fully explore the potential of distributed drive electric vehicle, an integrated coordination control method consists of model predictive control (MPC) and speed tracking control for trajectory tracking is proposed in this paper. Firstly, the vehicle dynamics model including the slip ratio of each wheel is established. Then, a multi-objective function of the MPC controller is established based on the principle of minimum tracking error, control vector, and control increment. And the optimal control sequences are obtained by optimizing the solution and correcting the feedback of the MPC, which satisfy both the actual kinematic constraints and the actuator performance constraints. The steering angle signal is sent to the steering motor directly, and the torque signal of each wheel which is obtained by superimposing the torque value output by the MPC controller and speed tracking controller is sent to the driving motor simultaneously. Finally, the proposed method is validated by using MATLAB/Simulink-Carsim co-simulation on different roads with conventional and severe pavement conditions. The simulation results show that the designed integrated coordination controller has obvious advantages in terms of tracking accuracy and body attitude stability during the course of lane change.

中文翻译：

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分布式驱动电动汽车轨迹跟踪的集成协调控制

为了充分发掘分布式驱动电动汽车的潜力，提出了一种由模型预测控制（MPC）和速度跟踪控制组成的轨迹跟踪综合控制方法。首先，建立包括每个车轮的滑移率的车辆动力学模型。然后，基于最小跟踪误差，控制向量和控制增量的原理，建立MPC控制器的多目标功能。通过优化解决方案并校正MPC的反馈来获得最优控制序列，该控制序列既满足实际运动学约束，又满足执行器性能约束。转向角信号直接发送到转向电机，通过将MPC控制器和速度跟踪控制器输出的扭矩值相叠加而获得的每个车轮的扭矩信号被同时发送到驱动马达。最后，在常规路面和恶劣路面条件下，通过在不同道路上使用MATLAB / Simulink-Carsim联合仿真对所提出的方法进行了验证。仿真结果表明，所设计的集成协调控制器在换道过程中的跟踪精度和身体姿态稳定性方面具有明显的优势。