【摘要】 为提高自适应巡航系统(Adaptive Cruise Control,ACC)的综合性能,通过对跟驰性能、安全性、燃油经济性以及乘客舒适性进行分析,作为系统的控制约束,并引入了基于驾驶数据的车头时距。采用了分层控制的架构,并基于模型预测控制理论(Model Predictive Control,MPC)设计了上层控制器。提出了一种可以根据当前行驶工况来对目标函数中的权重进行实时再分配的策略(Dynamic Weight Adjustment Strategy,DWAS),来解决传统固定权重在多工况下表现差的情况。实车实验表明,在复杂的多个工况下,所提出的权重可变的MPC控制器在保证跟驰性能和安全性的前提下,提高了燃油经济性和舒适性。更多还原

【Abstract】 To improve the performance of the adaptive cruise control(ACC), the tracking capability, safety, ride comfort and fuel economy are analyzed and introduced as the control constraints of the system. A headway time based on the driving data is also introduced as a system input. The ACC system is designed in layered architecture and the upper controller is based on the model predictive control(MPC). A dynamic weight adjustment strategy(DWAS) of the objective function is proposed according to the current driving condition to solve the problem of poor performance of the traditional constant weight in various driving conditions. The results show that the proposed MPC controller with dynamic weight adjustment strategy can improve fuel economy and comfort under complex driving conditions while ensuring the tracking capability and safety.更多还原