行星式混合动力客车的模型预测动态协调控制

行星式混合动力客车在驱动模式切换时会产生较大冲击度,以往基于PID的控制器在模式切换过程中无法有效保证车辆驾驶平顺性.基于此问题,利用模型预测控制(Model Predictive Control,MPC)可以在线滚动优化获得最优控制序列的特点,提出了一种基于MPC的动态协调控制方法,实现发动机的启动控制.依据整车动力学方程和实车历史数据,在Matlab/Simulink平台中搭建基于数据驱动的发动机模型和车辆闭环仿真模型,并将发动机启动过程视为受约束的多目标优化问题,根据系统状态空间方程和优化问题设计基于数据驱动的模型预测控制器,在纯电动模式向混合动力模式切换过程中,与传统基于PID的控制方法以及被动切换展开对比.仿真结果表明,在保证车辆动力性的前提下,相比于PID控制方法和被动切换,在模式切换过程中,基于MPC的动态协调控制方法不仅可以实现发动机的正常启动,还能大幅度降低峰值冲击度,同时使车辆良好地跟随目标车速.本文提出的模型预测控制器可以降低整车冲击度,保证车辆模式切换时的平顺性.

Model predictive dynamic coordinated control of planetary hybrid electric bus

Planetary hybrid electric buses usually have a great jerk while the drive mode switched. PID-based controller could not effectively ensure vehicle ride comfort during the mode switching process. Model predictive control(MPC) ,which can obtain optimal control sequences by online rolling optimization, is used to solve this issue, and a dynamic coordination control method based on MPC is proposed to start the engine. Based on the vehicle dynamic equations and vehicle historical data, the data-driven engine model and the closed-loop simulation model are set up in the Matlab/Simulink. Taking the start-up process of the engine as a constrained multi-objective optimization problem, the model predictive controller is designed according to the system state space equation and optimization problem. In the process of switching from the pure electric mode to the hybrid mode, the model predictive controller is compared with the traditional PID-based control method and without control. The simulation results demonstrate that under the premise of ensuring the dynamic performance of the vehicle, compared with the PID control and without control, during the mode switching process, the dynamic coordinated control method based on MPC can not only achieve the normal start of the engine, but also greatly reduce the peak jerk and also make the vehicle follow the target speed well.