分布式驱动电动汽车自适应巡航控制策略研究

Research on Adaptive Cruise Control Strategy of Distributed Driving Electric Vehicles

以分布式驱动汽车为研究对象,针对多目标协同的自适应巡航问题,应用非线性可变车头时距模型,对坡道、弯道工况设计了间距补偿策略,提高实际车间距离信号的准确性;综合考虑车辆行驶安全性,舒适性,节能性,设计了基于模型预测控制(Model predictive control,MPC)算法、分层控制的自适应巡航控制(Adaptive cruise control,ACC)系统。基于变步长离散化的方法改进ACC系统多目标协同上层控制算法,在保证较长预测时域的基础上提高系统的精确性和实时性。下层控制器中建立逆驱动系统模型、逆制动系统模型,制动/驱动切换逻辑,以车辆整体驱动效率最优为目标设计了期望力矩分配策略。在CarSim/Simulink搭建仿真环境验证了所设计策略的有效性。

Taking distributed driven vehicle as research object,aiming at the adaptive cruise problem of multi-objective coordination,the nonlinear variable time headway model was applied to design the spacing compensation strategy for the rampway and curve road conditions,which improved the accuracy of the distance signal of the actual workspace.The adaptive cruise control(ACC)system based on model predictive control(MPC)algorithm and layered control was designed considering vehicle safety,comfort and energy saving.The variable step size discretization method is used to improve ACC system multi-objective cooperative upper controller,enhancing the accuracy and real-time performance of system.In the lower controller,the inverse drive system model,the inverse brake system model,and the brake switch/drive logic were established,and the expected torque distribution strategy was designed to optimize the overall driving efficiency of the vehicle.The simulation environment was built in CarSim/Simulink to verify the effectiveness of the designed strategy.