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  • 标题:Optimized Fuzzy Logic Controller for Responsive Charging of Electric Vehicles
  • 本地全文:下载
  • 作者:Soumyadeep Nag ; Kwang. Y. Lee
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2019
  • 卷号:52
  • 期号:4
  • 页码:147-152
  • DOI:10.1016/j.ifacol.2019.08.170
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper contributes to the theme of intelligent integration of energy storage and the control of prosumer resources. The paper illustrates the use of a zero-order Sugeno fuzzy model to perform bidirectional real power control from an electric vehicle (EV), i.e., vehicle to grid (V2G) and grid to vehicle (G2V). The paper proposes an initial design of the fuzzy logic controller (FLC) following which the FLC is optimized using genetic algorithm (GA) for better performance under varying charging speed requirements of the user and better efficiency. A perturb and observe (P&O) algorithm based reactive power control is also proposed for voltage support through these EV chargers. The designed FLC can not only respond to grid conditions based on the time of use (TOU) but also to users charging speed requirements. Also, the initial design of an FLC may not suit a particular user’s requirement but can be optimized to meet the requirements.
  • 关键词:KeywordsEnergy storageenergy management systemsfuzzy controlgenetic algorithmsdistribution networkselectric vehicleefficiency enhancementreactive power
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