Yingwei Zhao, Zhen Wang, Yunying Man, H. Wen, Wen Han, Peiyao Wang
{"title":"Intelligent charging recommendation model based on collaborative filtering","authors":"Yingwei Zhao, Zhen Wang, Yunying Man, H. Wen, Wen Han, Peiyao Wang","doi":"10.1109/ICETCI53161.2021.9563497","DOIUrl":null,"url":null,"abstract":"In recent years, the development of new energy vehicles in the world has entered the industrial scale, but electric vehicles (EVs) have the disadvantage of short driving range due to the capacity of the battery, which need to supplement electric energy in charging stations. Although the number of charging piles for EVs is increasing day by day, its growth rate has not caught up with the charging demand for EVs. In order to provide personalized charging service for users with convenient power consumption and efficient charging, a set of intelligent recommendation model for EV charging is proposed based on collaborative filtering algorithm, which provides optimal charging method based on the user's historical behavior data.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETCI53161.2021.9563497","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In recent years, the development of new energy vehicles in the world has entered the industrial scale, but electric vehicles (EVs) have the disadvantage of short driving range due to the capacity of the battery, which need to supplement electric energy in charging stations. Although the number of charging piles for EVs is increasing day by day, its growth rate has not caught up with the charging demand for EVs. In order to provide personalized charging service for users with convenient power consumption and efficient charging, a set of intelligent recommendation model for EV charging is proposed based on collaborative filtering algorithm, which provides optimal charging method based on the user's historical behavior data.