CONDITIONAL OPTIMIZATION OF VESSEL CONTROLS WITH WIND ADDITIONAL PROPULSION SYSTEM
https://doi.org/10.33815/2313-4763.2025.2.31.030-040
Abstract
The maritime industry is facing significant challenges due to increasingly stringent legislative requirements for reducing emissions of harmful substances into the atmosphere and mitigating climate change. Among the wide range of technologies and fuel solutions considered in this context, one of the most promising is wind additional propulsion systems (WAPS), which can significantly reduce fuel consumption by ships and, as a result, reduce emissions of greenhouse gases and other harmful substances into the atmosphere. At present, wind propulsion systems such as WindWings, Wind Challenger, CWS are already in operation on ships including Pyxis Ocean, Berge Olympus, Shofu Maru, Windcoop and others. The WindWings system does not require auxiliary power for operation and has a built-in feathering function to manage sail performance in different weather conditions. The Wind Challenger system uses advanced patented technologies that allow the determination of wind direction and speed in real time, providing fully automatic control of extending, retracting, compressing and rotating sails. These and other wind turbines operate autonomously, independently of the vessel motion control system. The object of the research is the process of finding optimal controls for the combined structure of the vessel's actuators, which includes traditional actuators (propeller, rudder) and additional wind turbines. A method for controlling the movement of a vessel with additional wind turbines has been developed, which allows for further reduction in fuel consumption. This is achieved by finding optimal controls for the combined structure of the vessel's actuators by solving the problem of conditional optimization with equalities and inequalities in the on-board computer of the automatic control system. Equalities ensure the creation of the forces and moments necessary to maintain the given motion, and inequalities take into account the permissible ranges of control changes. The results obtained can be used in the development of mathematical support for autonomous vessel control systems or mathematical support for automatic control modules in automated systems.
References
2. Tony Glatz. Analyzing the Kinematics of Rotor Sails, Research Gate (2021). https://www.researchgate.net/publication/348420252_Analyzing_the_Kinematics_of_Rotor_Sails.
3. Данилов О. (2024). Вантажне судно Pyxis Ocean з жорсткими вітрилами завершило шестимісячні випробування. Вітрила економлять у середньому 3 тонни палива на день. Українська правда. https://mezha.ua/2024/03/21/pyxis-ocean-windwings-test-end/.
4. Ship kite propulsion system, Nautic expo connect (2025). https://www.nauticexpo.com/boat-manufacturer/ship-kite-propulsion-system-48507.html.
5. David Tyler (2014). The design of soft wing sails for cruising. https://www.boatdesign.net/threads/the-design-of-soft-wing-sails-for-cruising.49425/
6. Holloway, J. (2013). Vindskip ship concept uses the hull as a sail, New Atlas. https://newatlas.com/vindskip-wind-ship/29101/.
7. Carlson, O., Nilsson, P. (2015). Wind Turbines on Ships, Chalmers Publication Library. https://publications.lib.chalmers.se/records/fulltext/217076/local_217076.pdf .
8. Amy Peacock (2023). Pioneering wind-powered cargo ship charts course for greener shipping. https://www.dezeen.com/2023/08/22/pyxis-ocean-windwings-wind-powered-cargo-ship/.
9. Can Emir (2023). Berge Bulk’s Berge Olympus: A wind-powered marvel for greener oceans, Transportation. https://interestingengineering.com/innovation/berge-bulks-berge-olympus-wind-power?ysclid=mj2k50t8xn606954660.
10. Buitendijk, М. (2024). Wind Challenger saves fuel for coal carrier Shofu Maru, SWZ|Maritime. https://swzmaritime.nl/news/2024/05/23/wind-challenger-saves-fuel-for-coal-carrier-shofu-maru/.
11. Malayil, J. (2024). World-first wind-powered containership to have 11,300 sq ft total sail area, Interesting Engeneering, 2025. https://interestingengineering.com/innovation/world-first-open-hatch-sail-powered-containership?ysclid=mj2oa6lyrc348910409.
12. Suction Wings Wind-Assisted Propulsion in the Marine Industry: An Overview, Nautical Voice (2024). https://nauticalvoice.com/suction-wings-wind-assisted-propulsion-in-the-marine-industry-an-overview/21754/.
13. Wind Challenger. The Wind Assisted Ship Propulsion System. https://www.mol-service.com/en/services/energy-saving-technologies/wind-challenger.
14. Zinchenko, S., Kyrychenko, K., Grosheva, O., Nosov, P., Popovych, I., Mamenko, P. (2023). Automatic reset of kinetic energy in case of inevitable collision of ships, IEEE Xplore, pp. 496–500, 13th International Conference on Advanced Computer Information Technologies (ACIT), Wrocław, Poland. https://doi.org/10.1109/ACIT58437.2023.10275545. https://ieeexplore.ieee.org/ document/10275545.
15. Zinchenko, S. N., Lyashenko, V. G., Grosheva, O. A. (2018). Synthesis of optimal control of a vessel with boundary conditions, Scientific Bulletin of KhSMA, No. 1(18). http://journals.ksma.ks.ua/nvksma/article/view/502/440.
16. Zinchenko, S. N., Lyashenko, V. G., Shalaeva, A. A. (2017). Assessment of the maneuverability of a vessel using a neural network model synthesized in the process of its regular operation, Materials of the IV international scientific and practical conference "Life Safety in Transport and Production Education, Science, Practice", Kherson, September 14–16, pp. 236–240.
17. Zinchenko, S. N., Lyashenko, V. G. (2017). Using a neural network model of a ship to solve control problems, Scientific Bulletin of the KhSMA No. 2 (17), pp. 231–237. http://journals.ksma.ks.ua/nvksma/article/view/587/524.
18. Zinchenko, S. M., Mateychuk, V. M., Lyashenko, V. G. (2018). Using modeling information systems for the development and testing of automatic vessel movement control systems, Materials of the V MNPK "Life Safety in Transport and Production: Education, Science, Practice", Kherson, September 13-15, pp. 27–29.
19. Lübbecke, E., Lübbecke, M. E., Möhring, R. (2019). Ship Traffic Optimization for the Kiel Canal, Operations Research, Vol. 67, No. 3. https://doi.org/10.1287/opre.2018.1814.
20. Jia, Q., Li, R., Li, J., Li, Zh., Liu, J. (2023). Vessel traffic scheduling optimization for passenger RoRo terminals with restricted harbor basin, Ocean & Coastal Management, Volume 246, 106904. https://doi.org/10.1016/j.ocecoaman.2023.106904.
21. Wang, K., Yan, X., Yuan, Yu., Jiang, X., Lin, X., Negenborn, R. R. (2018). Dynamic optimization of ship energy efficiency considering time-varying environmental factors, Transportation Research Part D: Transport and Environment, Volume 62, July 2018, Pages 685–698. https://doi.org/10.1016/j.trd.2018.04.005.
22. Farzanegan, B., Esmailian, E., Menhaj, M. B. (2019). A data-driven method for optimal control of ship motions for safe crew transfer to offshore wind turbines, Applied Ocean Research, Vol. 90, September 2019, 101847. https://doi.org/10.1016/j.apor.2019.06.004.
23. Miyusov, M. V., Kryvyi, O. F. (2024). Optimal control of the combined propulsion system of a vessel with wind propulsors, Судноводіння | Shipping & Navigation. https://doi.org/10.31653/2306-5761.36.2024.116-130.
24. Inegiyemiema, M., Robinson, U. A., Eluku, D. A. (22025). Performance Investigation of the Hybrid Propulsion System of Tanker Vessel: A Case Study of Diesel and Wind Sail, The Journal of Scientific and Engineering Research 12(7):63–74.
25. Song J., Tan Yi., Zhang L., Liu Sh. (2025). An Optimal Energy‐Saving Coordination Control System for Sail‐Propeller of Wind‐Assisted Ships, IET Intelligent Transport Systems 19(1). https://doi.org/10.1049/itr2.70090.
