Abstract
This paper presents an innovative approach to the design of a forthcoming, fully electric-powered cargo vessel. This work begins by defining problems that need to be solved when designingvessels of this kind. Using available literature and market research, a solution for the design of apower management system and a battery management system for a cargo vessel of up to 1504 TEUcapacity was developed. The proposed solution contains an innovative approach with three parallelenergy sources. The solution takes into consideration the possible necessity for zero-emission workwith the optional function of operation as an autonomous vessel. Energy storage system based onlithium-ion battery banks with a possibility of expanding the capacity is also described in this work asit is the core part of the proposed solution. It is estimated that the operation range for zero-emissionwork mode of up to 136 nautical miles can be achieved through the application of all fore-mentioned parts.
Citations
-
8
CrossRef
-
0
Web of Science
-
9
Scopus
Authors (4)
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/en14041048
- License
- open in new tab
Keywords
Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
ENERGIES
no. 14,
ISSN: 1996-1073 - Language:
- English
- Publication year:
- 2021
- Bibliographic description:
- Karkosiński D., Rosiński W. A., Deinrych P., Potrykus S.: Onboard Energy Storage and Power Management Systems forAll-Electric Cargo Vessel Concept// ENERGIES -Vol. 14,iss. 14 (2021), s.1048-
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/en14041048
- Verified by:
- Gdańsk University of Technology
seen 166 times
Recommended for you
Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings
- M. Arun,
- T. T. Le,
- D. Barik
- + 6 authors
Innovative system for energy collection and management integrated within a photovoltaic module
- W. Grzesiak,
- P. Maćków,
- T. Maj
- + 6 authors
Energy Management for PV Powered Hybrid Storage System in Electric Vehicles Using Artificial Neural Network and Aquila Optimizer Algorithm
- N. Narasimhulu,
- R. S. R. Krishnam Naidu,
- P. Falkowski-Gilski
- + 2 authors