基于边缘计算的电动汽车换电电池冗余度建模分析

针对电动汽车换电站电池冗余度过高，充电成本过高的问题，研究基于边缘计算的电动汽车换电电池冗余度建模分析。结合边缘计算与云计算技术，建立电动汽车换电电池冗余度分析的边缘计算平台，利用边缘节点A采集电动汽车用电信息，将采集数据上传至云平台，云平台利用电动汽车换电电池充电优化控制模型分析边缘节点B关联电动汽车换电电池冗余度，利用自适应遗传算法求解模型，实现电动汽车换电电池充电优化。实验结果表明，该模型可有效分析电动汽车换电电池冗余度，将该模型应用于电动汽车换电站，换电站月充电费用降低幅度大于13%。

Modeling and Analysis of Redundancy of Battery Replacement for Electric Vehicles Based on Edge Computing

In order to solve the problem of high battery redundancy and high charging cost in electric vehicle power station, this paper studies the modeling and analysis of battery redundancy based on edge calculation. Combined with edge computing and cloud computing technology, an edge computing platform for analyzing the redundancy of electric vehicle battery is established. The edge node a is used to collect the electric vehicle electricity information, and the collected data is uploaded to the cloud platform. The cloud platform uses the electric vehicle battery charging optimization control model to analyze the edge node B associated with the electric vehicle battery redundancy, and uses adaptive genetic algorithm The model is solved to realize the optimization of battery charging. The experimental results show that the model can effectively analyze the battery redundancy of electric vehicle, and the monthly charging cost of the battery can be reduced by more than 13% when the model is applied to the electric vehicle exchange station.