Prototyping Design and Optimization of Smart Electric Vehicles/Stations System using ANN

被引:0
|
作者
Elkasrawy, Mohamed A. [1 ,2 ]
Hassan, Ahmed [2 ,3 ]
Abdellatif, Sameh O. [2 ,3 ]
Ebrahim, Gamal Abdel Shafy [4 ]
Ghali, Hani A. [2 ,3 ]
机构
[1] British Univ Egypt BUE, Fac Engn, Renewable Energy Programme, Cairo 11387, Egypt
[2] British Univ Egypt BUE, FabLab, Ctr Emerging Learning Technol CELT, Cairo 11387, Egypt
[3] British Univ Egypt BUE, Fac Engn, Elect Engn Dept, Cairo 11387, Egypt
[4] Ain Shams Univ, Fac Engn, Comp Engn Dept, Cairo, Egypt
关键词
Real-time algorithms; Physical realization; Electric vehicles stations; Queuing delay optimization; Artificial neural network (ANN) algorithm; VEHICLES;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper demonstrates an experimental attempt to prototype electric vehicle charging station's (EVCS) decision-making unit, using artificial neural network (ANN) algorithm. The algorithm acts to minimize the queuing delay in the station, with respect to the vehicle state of charge (SOC), and the expected arrival time. A simplified circuit model has been used to prototype the proposed algorithm, to minimize the overall queuing delay. Herein, the worst-case scenario is considered by having number of electric vehicles arriving to the station at the same time greater than the charging points available in the station side. Accordingly, the optimization technique was applied to reduce the mean charging time of the vehicles and minimize queuing delay. Results showed that this model can help in reducing the queuing delay by around 20% of the mean charging time of the station, while referring to a bare model without ANN algorithm as a reference.
引用
收藏
页码:485 / 491
页数:7
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