Electric vehicles (EVs) are becoming increasingly popular, but the frequent charging and large charging latency remain major obstacles to the EV industry. This article focuses on the charging scheduling of on-the-move EVs in a transportation network to minimize EVs’ charging latency, including driving time to charging stations (CSs), wait time and charging time. We formulate this charging scheduling problem as a graphical game to characterize the strong couplings of charging latency among neighboring EV players. Specially, we investigate correlated equilibrium (CE) to describe the joint strategies of EV players, which is expected to further reduce the charging latency of EVs compared with Nash equilibrium (NE). It is shown that CE always exists in a finite game, and can be found by linear programming tools. In addition, we propose a method of wait time prediction, which can improve the prediction accuracy by combining the data of deterministic EV arrivals and the stochastic property of potential EV arrivals. Simulation studies are used to examine the performance of the proposed game-based approach, the efficiency of CE, the preciseness of our proposed wait time prediction method, the impacts of CS deployment on EVs’ charging latency, etc. We can draw a conclusion that our method has apparent advantages in situations where the locations of EV players are in dense manners.

中文翻译：

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电动汽车充电调度的图形游戏方法：相关平衡和延迟最小化


电动汽车（EV）越来越受欢迎，但频繁的充电和较长的充电延迟仍然是电动汽车行业的主要障碍。本文重点研究交通网络中移动电动汽车的充电调度，以最大限度地减少电动汽车的充电延迟，包括前往充电站 (CS) 的行驶时间、等待时间和充电时间。我们将这个充电调度问题制定为图形游戏，以表征相邻电动汽车玩家之间充电延迟的强耦合。特别地，我们研究了相关均衡（CE）来描述电动汽车参与者的联合策略，与纳什均衡（NE）相比，这有望进一步减少电动汽车的充电延迟。结果表明，CE在有限博弈中始终存在，并且可以通过线性规划工具找到。此外，我们提出了一种等待时间预测方法，该方法可以通过结合确定性电动车到达数据和潜在电动车到达的随机性来提高预测精度。仿真研究用于检验所提出的基于游戏的方法的性能、CE的效率、我们提出的等待时间预测方法的精确性、CS部署对电动汽车充电延迟的影响等。我们可以得出这样的结论：我们的方法在电动汽车玩家位置密集的情况下具有明显的优势。