电力系统自动化2024，Vol.48Issue(7)：159-168,10.DOI:10.7500/AEPS20230730001
车联网环境下电动汽车主动充电引导模型
Active Charging Guidance Model of Electric Vehicles Based on Internet of Vehicles
摘要
Abstract
In order to adapt to the rapid growth of electric vehicles (EVs) and charging demand, this paper proposes an active charging guidance model of EVs based on the Internet of vehicles by using the improved A* path planning algorithm and the queuing theory from the perspective of EV users. Firstly, incorporating the traffic light waiting time and the no-backtracking condition, the A* path planning algorithm is improved to update the spatiotemporal state matrix of the road network using the actual road network state information, which can optimize the EV driving path in real time and obtain the EV traveling time for charging. Secondly, the deep belief network (DBN) is utilized to predict the short-time arrival numbers of EVs at the charging station, and the EV waiting time for charging is predicted based on the M/G/k model using the queuing theory. Finally, the active charging guidance model of EVs is constructed to minimize the traveling time and waiting time of EVs for charging. Taking the central area of Nanjing, China as an example, the effectiveness of the proposed active charging guidance model is verified. The proposed algorithm can improve the utilization rate of charging piles and reduce the comprehensive charging time of EV users.关键词
车联网/电动汽车/主动充电引导/排队论/路径规划Key words
Internet of vehicles/electric vehicle(EV)/active charging guidance/queuing theory/path planning引用本文复制引用
袁晓冬,甘海庆,王明深,滕欣元,阮文骏,龙寰..车联网环境下电动汽车主动充电引导模型[J].电力系统自动化,2024,48(7):159-168,10.基金项目
国家重点研发计划资助项目(2021YFB2501600). This work is supported by National Key R&D Program of China(No.2021YFB2501600). （2021YFB2501600）
