河南科技大学学报：自然科学版

在城市路况下,电池和超级电容复合电源电动汽车会对信号灯判断不准确而频繁起停,造成额外的能量消耗。基于智能交通系统中预知交通信号信息的应用场景,本文提出了一种分层能量管理方法。首先,根据交通信号信息,上层车速设计策略优化车速,得到车辆经济参考车速,避免车辆在信号灯区域频繁起停。其次,基于经济参考车速,设计了一种基于非线性模型预测控制的下层能量管理策略,合理分配电池及超级电容的功率输出,并有效跟踪经济参考车速,降低电池功率的变化率。最后,对所提出的车速设计和能量管理策略进行仿真分析,并搭建实验平台进行验证。研究结果表明:分层能量管理策略使等效燃油经济性提高了3.24%,降低了电池能耗,并且减少了车辆急加速或急减速情况,提高了驾驶舒适性。

Under urban road conditions,due to the inability to obtain the accurate traffic information ahead,the battery and supercapacitor hybrid electric vehicles inevitably stopped frequently with inaccurate signal lights judgment,which may cause additional energy consumption. Based on the application scenarios of predicting traffic signal information in intelligent transportation systems,a hierarchical energy management method was proposed. Firstly,according to the traffic signal information,the upper-level vehicle speed design strategy optimized the vehicle speed and obtained the economic reference speed of the vehicle to avoid frequent start and stop of the vehicle in the signal light area. Secondly,based on the economic reference vehicle speed,a lower-level energy management strategy using nonlinear model predictive control was designed to reasonably allocate the power output of batteries and supercapacitor,to track the economic reference vehicle speed,and to reduce the rate of change of battery power.Finally,the proposed vehicle speed design and energy management strategy were simulated and analyzed,and an experimental platform was built for verification.The results show that based on the proposed hierarchical energy management method,the equivalent fuel economy is increased by 3.24%,and the battery energy consumption is reduced.In addition,the rapid acceleration or deceleration of the vehicle is reduced,and the driving comfort is improved.