基于物联网与GS算法的电动汽车充电推荐系统

Electric Car Charging Recommendation System Based on Internet of Things and GS Algorithm

目前电动汽车充电问题的解决方案只局限于就近原则或偏好原则,这两种选择方案或多或少会带来电车剩余电量撑不到充电站、到达充电站后排队等候时间长的问题,因而引发人们对于电动汽车的“里程焦虑”。为了解决该问题,将物联网和盖尔-沙普利算法相结合,根据车主的个人喜好以及车辆运行情况计算出车辆预约充电站的最优匹配,在有效减少排队时间的同时增加充电站的吞吐量。对三种选择方案(就近原则、偏好原则、GS算法)进行比较,得出GS算法可以实现车辆和充电站的最优匹配。

At present,the solution to the charging problem of electric cars is limited to the principle of proximity or preference.These two options will more or less lead to the problem that the remaining power of the electric car cannot arrive at the charging station and the queue time is long after arriving at the charging station,which leads to people’s concerns about“Mileage Anxiety”of electric car.In order to solve this problem,the system combines the Internet of Things and the Gale-Shapley algorithm to calculate the optimal matching of the car’s reserved charging station according to the owner’s personal preferences and car operation conditions.Increase the throughput of the charging station while reducing the queue time.This paper compares three solutions:proximity principle,preference principle,and GS algorithm,it can be concluded that the GS algorithm can achieve the optimal matching of cars and charging stations.