A method of chained recommendation for charging piles in internet of vehicles

Abstract

With the popularization of new energy electric vehicles (EVs), the recommendation algorithm is widely used in the relatively new field of charge piles. At the same time, the construction of charging infrastructure is facing increasing demand and more severe challenges. With the ubiquity of Internet of vehicles (IoVs), inter-vehicle communication can share information about the charging experience and traffic condition to help achieving better charging recommendation and higher energy efficiency. The recommendation of charging piles is of great value. However, the existing methods related to such recommendation consider inadequate reference factors and most of them are generalized for all users, rather than personalized for specific populations. In this paper, we propose a recommendation method based on dynamic charging area mechanism, which recommends the appropriate initial charging area according to the user's warning level, and dynamically changes the charging area according to the real-time state of EVs and charging piles. The recommendation method based on a classification chain provides more personalized services for users according to different charging needs and improves the utilization ratio of charging piles. This satisfies users' multilevel charging demands and realizes a more effective charging planning, which is beneficial to overall balance. The chained recommendation method mainly consists of three modules: intention detection, warning levels classification, and chained recommendation. The dynamic charging area mechanism reduces the occurrence of recommendation conflict and provides more personalized service for users according to different charging needs. Simulations and computations validate the correctness and effectiveness of the proposed method.