QoS guaranteed online management of battery swapping station under dynamic energy pricing. Issue 3 (13th March 2019)

• Record Type: Journal Article
• Authors: Wang, Luhao; Pedram, Massoud
• Is Part Of: IET cyber-physical systems. Volume 4:Issue 3(2019)
• Page Start: 259
• Page End: 264
• Publication Date: 2019-03-13
• Subjects: secondary cells -- optimisation -- quality of service -- battery management systems -- scheduling -- battery powered vehicles -- pricing -- electric vehicles; fully charged ones -- EVs -- batteries -- minimising electrical energy costs -- realistic BSS framework -- different battery state‐of‐charges -- battery charging scheduling problem -- dynamic energy pricing -- multilevel BSS system architecture -- online optimal BSS control problem -- offline optimal BSS design problem -- amortised battery costs -- total charging energy cost -- battery swapping station -- relatively short driving distance -- long battery charging time -- fast EV battery recharging -- partially charged ones
• DOI: 10.1049/iet-cps.2018.5041
• Languages: English
• ISSNs: 2398-3396

Abstract

Abstract : Further popularisation of electric vehicles (EVs) is hindered by their relatively short driving distance and long battery charging time. To overcome these shortcomings, the battery swapping station (BSS) has been proposed as a means of satisfying the increasing demands for fast EV battery recharging. At a BSS, (partially) depleted batteries from EVs can be replaced with partially or fully charged ones almost instantaneously. Recharging scheduling and maintenance of batteries are done by the operator of BSS, with the target of minimising electrical energy costs while satisfying customer demands. In this study, the authors consider a realistic BSS framework in which EVs can arrive at BSS with time of day dependent rates having different battery state‐of‐charges. They investigate the battery charging scheduling problem in the BSS under a dynamic energy pricing. They solve (i) an online optimal BSS control problem to minimise the energy cost with a quality‐of‐service (QoS) guarantee, and (ii) an offline optimal BSS design problem to determine the optimal number of stored batteries so as to achieve a desirable tradeoff between flexibility in charging and amortised battery costs. The experimental results show that the total charging energy cost can be reduced significantly under different traffic scenarios.