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Research on SFLA-Based Bidirectional Coordinated Control Strategy for EV Battery Swapping Station

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Key Laboratory of Hydraulic Machinery Transients (Wuhan University), Ministry of Educationy, Wuhan 430072, China.
School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China.
School of Urban Rail Transit, Changzhou University, Changzhou 213164, China.

Computers, Materials & Continua 2017, 53(4), 343-356. https://doi.org/10.3970/cmc.2017.053.343

Abstract

As a good measure to tackle the challenges from energy shortages and environmental pollution, Electric Vehicles (EVs) have entered a period of rapid growth. Battery swapping station is a very important way of energy supply to EVs, and it is urgently needed to explore a coordinated control strategy to effectively smooth the load fluctuation in order to adopt the large-scale EVs. Considering bidirectional power flow between the station and power grid, this paper proposed a SFLA-based control strategy to smooth the load profile. Finally, compared simulations were performed according to the related data. Compared to particle swarm optimization (PSO) method, the presented SFLA-based strategy can effectively lower the peak-valley difference with the faster convergence rate and higher convergence precision. It is important for the swapping station that energy exchanging mode can supply energy for large-scale EVs with a smoother load profile than one-way charging mode.

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APA Style
Zhao, G., Guo, J., Qiang, H. (2017). Research on sfla-based bidirectional coordinated control strategy for EV battery swapping station. Computers, Materials & Continua, 53(4), 343-356. https://doi.org/10.3970/cmc.2017.053.343
Vancouver Style
Zhao G, Guo J, Qiang H. Research on sfla-based bidirectional coordinated control strategy for EV battery swapping station. Comput Mater Contin. 2017;53(4):343-356 https://doi.org/10.3970/cmc.2017.053.343
IEEE Style
G. Zhao, J. Guo, and H. Qiang, “Research on SFLA-Based Bidirectional Coordinated Control Strategy for EV Battery Swapping Station,” Comput. Mater. Contin., vol. 53, no. 4, pp. 343-356, 2017. https://doi.org/10.3970/cmc.2017.053.343



cc Copyright © 2017 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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