基于DMPC的多车协同自适应巡航控制研究

Research on Multi-vehicle Cooperative Adaptive Cruise Control Based on DMPC

针对多车协同自适应巡航控制系统(CACC)中车辆跟驰距离波动大的问题,提出了一种分布式模型预测控制(DMPC)策略。采用分层控制的思想对CACC系统进行控制。控制器分为上位控制器和下位控制器。上位控制器根据车队状态计算车辆的期望加速度,下位控制器根据期望加速度控制车辆的节气门开度和制动系统压力。首先,建立了车队的纵向动力学模型。其次,根据控制目标设计目标函数,使车队能够获得当前时刻的最优控制量。然后基于逆发动机模型和逆制动模型设计了下位控制器。最后,通过Carsim和MATLAB/Simulink的联合仿真,验证了所设计控制策略的有效性。结果表明,DMPC可以减小车辆跟驰距离误差的峰值、标准差和均方根值,提高跟驰稳定性。

To solve the problem of large fluctuation of vehicle following distance in cooperative adaptive cruise control(CACC),a distributed model predictive control(DMPC)strategy is proposed.The idea of hierarchical control,is performed to control the CACC system.The controller is divided into an upper controller and a lower controller.The upper controller calculates the expected acceleration of the vehicle according to the platooning state,and the lower controller controls the throttle and braking system pressure of the vehicle according to the expected acceleration.Firstly,the longitudinal dynamic model of vehicle platooning is established.Secondly,the objective function is designed according to the control objectives,so that the platooning can obtain the optimal control quantity at the current time.Then the lower controller is designed based on a reverse engine model and a reverse braking model.Finally,the effectiveness of the designed control strategy is verified by the co-simulation of Carsim and MATLAB/Simulink.The results show that DMPC can reduce the peak value,the standard deviation and the root mean square of vehicle following distance error and improve the following stability.