Journal of Marine Science and Engineering (Feb 2023)

Optimal SOC Control and Rule-Based Energy Management Strategy for Fuel-Cell-Based Hybrid Vessel including Batteries and Supercapacitors

  • Zeyu Ma,
  • Hao Chen,
  • Jingang Han,
  • Yizheng Chen,
  • Jiongchen Kuang,
  • Jean-Frédéric Charpentier,
  • Nadia Aϊt-Ahmed,
  • Mohamed Benbouzid

DOI
https://doi.org/10.3390/jmse11020398
Journal volume & issue
Vol. 11, no. 2
p. 398

Abstract

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Around the world, the development of electric vehicles is underway, including in maritime transportation. However, the development of clean energy vessels still has a long way to go. Fuel cells (FCs) are a relevant choice among the many clean energy sources to power clean energy vessels. However, due to the complex and drastic change in the shipload power, FCs need to be equipped with dynamic fast-response energy storage equipment to make up for it. For multiple energy storage devices connected in parallel, the state of charge (SOC) is not balanced, which affects their service life and the stability of the vessel microgrid, as well as slowing the speed and lowering the accuracy of SOC equalization. This paper proposes a distributed variable sag slope control strategy for vessels to improve SOC equalization, with a FC as the energy source and a battery and supercapacitor as the energy storage system (ESS). For the output power distribution problem of energy storage equipment caused by shipload power variation, a power distribution strategy with a variable filter time constant is used to improve the reasonableness of the output power distribution of energy-based lithium batteries and power-based supercapacitors. Meanwhile, this paper considers the power generation equipment’s service life and energy cost as the optimization objectives, considering the discharge depth of the energy storage equipment. Finally, a method based on the combination of the lithium battery SOC rule (the rule formulated according to the state of charge and load power change in energy storage equipment) and particle swarm optimization algorithm is proposed to solve this problem. The simulation results show that the proposed strategy improves the equalization speed and accuracy of the SOC of energy storage devices, fully realizes the characteristics of different energy storage devices, and reduces the life loss of energy storage devices.

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