摘要
为实现混合动力汽车的实时最优能量管理,提出一种基于智能网联的分层能量管理控制方法。上层控制器利用交通信号灯正时求解目标车速的范围,而采用快速模型预测控制(F-MPC)算法预测给定时间窗口内的最优目标车速序列。下层控制器根据最优目标车速序列,利用基于威兰斯线方法的等效燃油消耗最小策略(WLECMS)进行混合动力汽车能量管理。硬件在环试验结果表明,所提出的基于智能网联的上层控制器可避免混合动力汽车红灯停车,而F-MPC可实现与MPC相近的最优车速预测和燃油经济性,且每一时间步长的计算时间可缩短到MPC的7.2%;WL-ECMS可实现良好的车速跟随,百公里油耗与ECMS相当,且每一时间步长的计算时间可缩短到ECMS的1.48%。
In order to realize the real-time optimal energy management of hybrid electric vehicles （ HEVs）, a hierarchical energy management control scheme based on intelligent and connected vehicle technology is put for-ward. The upper layer controller utilizes traffic signal phase and timing to obtain the target speed range,and uses fast model predictive control （F-MPC） algorithm to predict the optimal target speed sequences over a given time window. According to the optimal target speed sequences,the lower layer controller utilizes Willans-Line-based e-quivalent consumption minimization strategy （ WL- ECMS） to fulfill the energy management of HEVs. The results of hardware- in- the-loop test show that with the intelligent and connected vehicle-based upper layer controller,HEVs can avoid red light stopping. The fuel economy with F-MPC is approximate to that of MPC and the calculation time for a single time step with F-MPC is reduced to 7. 2 % of that with MPC. WL-ECMS strategy can realize good speed tracking,its fuel economy is comparable with ECMS,and its calculation time for a single step is reduced to only 1. 48% of that with ECMS.
出处
《汽车工程》
EI
CSCD
北大核心
2017年第6期621-629,共9页
Automotive Engineering
基金
2012年国家新能源汽车技术创新工程(财建[2012]1095号)
2013年国家科技支撑计划课题专项资金(2013BAG08B01)资助
关键词
智能网联汽车
混合动力汽车
分层控制
快速模型预测控制
能量管理
intelligent and connected vehicles
HEVs
hierarchical control
fast model predictive con-trol
energy managemen
