An Electric Vehicle Charging Management Scheme Based on Publish/Subscribe Communication Framework

Yue Cao, Ning Wang, Kamel George, Kim Young-Jin

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)
4 Downloads (Pure)

Abstract

Motivated by alleviating CO$_2$ pollution, Electric Vehicle (EV) based applications have recently received wide interests from both commercial and research communities by using electric energy instead of traditional fuel energy. Although EVs are inherently with limited travelling distance, such limitation could be overcome by deploying public Charging Stations (CSs) to recharge EVs battery during their journeys. In this article, we propose a communication framework for on-the-move EV charging scenario, based on Publish/Subscribe (P/S) mechanism to disseminate necessary information about CSs to EVs. Concerning privacy issue, those EVs subscribing to such information could then locally make their individual decisions to select desired CSs for charging, rather than applying a centralized manner where private EV information is required to be released through communication. In this paper we propose a novel communication framework for on-the-move EV charging scenario, based on the Publish/Subscribe (P/S) mechanism for disseminating necessary CS information to EVs, in order for them to make optimized decisions on where to charge. A core part of our communication framework is the utilization of Road Side Units (RSUs) to bridge the information flow from CSs to EVs, which has been regarded as a type of cost-efficient communication infrastructure. Under this design, we introduce two complementary communication modes of signalling protocols, namely Push and Pull Modes, in order to enable the required information dissemination operation. Both analysis and simulation show the advantage of Pull Mode, in which the information is cached at RSUs to support asynchronous communication. We further propose a remote reservation service based on the Pull Mode, such that the CS-selection decision making can utilize the knowledge of EVs' charging reservation, as published from EVs through RSUs to CSs. Results show that both the performance at CS and EV sides are further improved based on using this anticipated information.
Original languageEnglish
JournalIEEE Systems Journal
Early online date14 Jul 2015
DOIs
Publication statusE-pub ahead of print - 14 Jul 2015

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