Abstract
The huge power requirements of future railway transportation systems require the usage of energy efficient strategies towards a more intelligent railway system. With the usage of on-board energy storage systems, it is possible to increase the energy efficiency of railways. In this paper, a top-level charging controller for the on-board energy storage system is proposed based on a fuzzy logic controller. As an optimization procedure to increase the energy efficiency of such charging controller, a genetic algorithm meta-heuristic is used to automatically tune the fuzzy rules weight. To validate the proposed controller, two sets of rules were defined, one considering only known rules and the other also considering all possible combinations of rules. As global results, the reduction of regenerated energy reached 30%, and the net energy consumption reduction is near 10%.
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Acknowledgments
The research leading to these results has received funding from the FCT – Fundação Ciência e Tecnologia – under grant PD/BD/128051/2016, supported by MCTES national funds and FSE funds through POCH program. This work was supported by UID/EEA/00147/2019 - Research Center for Systems and Technologies funded by national funds through the FCT/MCTES through national funds (PIDDAC).
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Morais, V.A., Afonso, J.L., Martins, A.P. (2020). Towards Smart Railways: A Charging Strategy for On-Board Energy Storage Systems. In: Afonso, J., Monteiro, V., Pinto, J. (eds) Sustainable Energy for Smart Cities. SESC 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-030-45694-8_3
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DOI: https://doi.org/10.1007/978-3-030-45694-8_3
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