An Electric Vehicle Charging Management Scheme Based on Publish/Subscribe Communication Framework
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 traveling distance, such limitat...
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Veröffentlicht in: | IEEE systems journal 2017-09, Vol.11 (3), p.1822-1835 |
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Sprache: | eng |
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Zusammenfassung: | 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 traveling distance, such limitation could be overcome by deploying public charging stations (CSs) to recharge EVs' battery during their journeys. 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 roadside 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 signal protocols, namely, push and pull modes, in order to enable the required information dissemination operation. Both analysis and simulation show the advantage of the 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 performances at CS and EV sides are further improved based on using this anticipated information. |
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ISSN: | 1932-8184 1937-9234 |
DOI: | 10.1109/JSYST.2015.2449893 |