基于大数据的纯电动汽车节能规划研究

Research on Energy Saving of EV Based on Big Data

近年来我国电动汽车产业快速发展,但是电动汽车在发展过程中面临很多问题,如充电后的续驶里程较短、充电设施分布不均匀。在考虑电动汽车行驶特性的基础上,对新能源汽车进行路径规划是城市交通发展亟待解决的问题。全面深入地对电动汽车运行、时间与电量、阻抗、充电的路径规划模型和最短路径搜索以及电动汽车路径选择、运行方案进行分析,通过构建运行时间和运行路径阈值约束下的总能耗最低混合整数规划模型,算法设计标号修改算法和标号设定算法相结合的两阶动态规算法。最终,通过实际测算电动汽车的能耗平均优化率达10.2%。

In recent years,Chinese EV industry has developed rapidly.However,electric vehicles still have many practical problems,including short driving range after charging and charging facilities distributed.Considering the driving characteristics of electric vehicles,path planning is an urgent problem to be solved in the development of transportation.This paper deeply analyzes electric vehicles operation,time and electric impedance,charging path planning model,path selection and operation scheme.The model is constructed through total energy consumption minimum mixed integer by time and battery capacity、path threshold,the algorithm is two order dynamic metric through design label modification and setting combined.Finally,the average optimization rate of energy consumption is 10.2%.