Towards an Efficient and Real-Time Scheduling Platform for Mobile Charging Vehicles

• Published in: Algorithms and Architectures for Parallel Processing Vol. 11336; pp. 402 - 416
• Main Authors: Liu, Qi, Li, Jinyang, Sun, Xiaoshan, Wang, Junjie, Ning, Yang, Zheng, Wei, Li, Jian, Liu, Hengchang
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2018; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Electric vehicle; Mobile charging vehicle; Scheduling strategy
• ISBN: 3030050564; 9783030050566
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-05057-3_31

With increasing environmental awareness from the society, electric vehicles (EVs) have been taking a steady increasing market share each year. Meanwhile, the development of the infrastructure of the public charging facilities for EVs is much more restricted compared to fossil-fuel vehicles. Moreover, the overall charging demand usually significantly varies in both spatial and time domains. As a result, the availability of public charging facilities usually do not match the exact demand during different hours of the day. In this paper, we introduce a new charging facility – mobile charging vehicles (MCVs), which carry batteries that can be used for charging other EVs. We propose three different scheduling strategies of MCVs and evaluate the performance through a real world EVs charging dataset. Our experiment shows that the addition of MCVs to current charging facilities greatly increases the overall charging efficiency, in both waiting time of EVs and the load rate of stations.