Aspects of improving the reliability of unmanned surface vehicles
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Published:
Sep 1, 2024
Keywords:
unmanned surface vehicles, maritime transport, energy supply systems, autonomous control systems, energy efficiency, solar panels, hybrid systems, reliability, sustainability, maritime technologies
Main Article Content
Abstract
The article presents a comprehensive study of power supply systems for unmanned surface vehicles (USVs) with an emphasis on their reliability, efficiency and sustainability. The current state of the art of power supply technologies is analyzed and the technical challenges associated with autonomous maritime operations are identified. The study evaluates various energy sources, including solar panels, lithium-ion and lithium- polymer batteries, and hybrid systems. The calculations predict energy consumption under different operational scenarios, emphasizing the need to develop effective energy management strategies and help design systems that can meet the specific energy needs of different missions. The results of the study provide practical recommendations for improving the energy efficiency, autonomy, and reliability of USVs, emphasizing the importance of innovation and collaboration in overcoming the challenges faced by the maritime industry.
Article Details
How to Cite
Burlachenko, D., Pasternak, O., Pulyaev, I., Zayats, S., Checha, O., & Scheniavskyi, G. (2024). Aspects of improving the reliability of unmanned surface vehicles. Herald of the Odessa National Maritime University, (73), 184-201. https://doi.org/10.47049/2226-1893-2024-2-184-201
Section
Ensuring the safety of navigation
References
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28. Melnyk O., Onishchenko O., Onyshchenko S., Voloshyn A., Kalinichenko Y., Rossomakha O., Naleva G., Rossomakha O. (2022). Autonomous Ships Concept and Mathematical Models Application in their Steering Process Control. TransNav, 16 (3), pp. 553-559. DOI: 10.12716/1001.16.03.18
2. Katsuras, Georgios, Dimitriou, Elias, Karavoltsos, Sotirios, Samios, Stylia- nos, Sakellari, Aikaterini, Mentzafo, A., Tsallas, Nikolaos, & Skoulos, Michael. (2024). Use of Unmanned Surface Vehicles (USVs) in Water Chemistry Research. Sensors, 24, 2809. DOI: 10.3390/s24092809.
3. Li, Chenmin, Zhao, Xu, Yu, Rongrong, Chen, Yehwa, & Lin, Fei. (2024). New Robust Control and Optimal Design for Fuzzy Unmanned Surface Vehicles (USVs). International Journal of Fuzzy Systems. DOI: 10.1007/ s40815-024- 01767-3.
4. Shimkhanda, Daniel, Yan, Shaolun, & Xiang, Xiangbo. (2024). Route Plan- ning Algorithms for Unmanned Surface Vehicles (USVs): A Comprehensive Analysis. Journal of Marine Science and Engineering, 12, 382. DOI: 10.3390/jmse12030382.
5. Shaaban, S., Abdellatif Hamed Ibrahim, Ahmed, Khaled, Dina, Ali, Gussien, Khaled, Mariam, & Elnaggar, Nurhan. (2021). Development of a Sustainable Unmanned Surface Vehicle (USV) for Search and Rescue Operations. International Undergraduate Research Conference, Cairo, Egypt. DOI: 10.21608/IUGRC.2021.246530.
6. Tan, Goge, Zhuang, Jiayuan, Zou, Jing, & Wang, Lei. (2022). Task Alloca- tion for Multiple Heterogeneous Unmanned Surface Vehicles (USVs) Based on a Self-Organizing Map. Applied Ocean Research, 126, 103262. DOI: 10.1016/j.apor.2022.103262.
7. Tan, Goge, Zhuang, Jiayuan, Zou, Jing, & Wang, Lei. (2023). Adaptive Path Planning for a Swarm of Heterogeneous Unmanned Surface Vehicles (USVs) Using the Fast Marching Square Method. Ocean Engineering, 268, 113432. DOI: 10.1016/j.oceaneng.2022.113432.
8. Ansari, Jamal, O'Donnell, Jacob, Fayza, Nashiyat, & Trace, Brian. (2020). Swarm of Waterborne Unmanned Surface Vehicles (USVs): A Review from Modeling to Field Implementation. International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. DOI: 10.1115/DETC2020-22702.
9. Boo, Sun. (2004). Conceptual Design Study of an Unmanned Surface Vehicle (USV) for the Korean Navy. Journal of the Korean Institute of Military Science and Technology, 7.
10. Katsuras, Georgios, Dimitriou, Elias, Karavoltsos, Sotirios, Samios, Stylia- nos, Sakellari, Aikaterini, Mentzafo, A., Tsallas, Nikolaos, & Skoulos, Michael. (2024). Water Quality of Watersheds in the Eastern Mediter- ranean Using Autonomous Unmanned Surface Vehicles (USVs). DOI: 10.20944/preprints202402.1125.v1.
11. Luo, Jing, Zhang, Yuhan, Zhuang, Jiayuan, & Su, Yumin. (2024). Intelligent Task Allocation and Planning for Unmanned Surface Vehicles (USVs) Using Self-Monitoring and Blocking Deployment Methods. Journal of Marine Science and Engineering, 12, 179. DOI: 10.3390/jmse12010179.
12. Liu, Wenwen. (2020). Reliable Multi-Sensor Data Fusion for Practical Navigation of Unmanned Surface Vehicles (USVs). University College London Conference.
13. Liu, Yiping, Zhang, Jianqiang, Sui, Bowen, & Zhang, Yuanyuan. (2024). Low-Activity Unmanned Surface Vehicle Formation for Obstacle Avoidance and Assembly: A Perturbed Fluid-Based Solution. Measurement and Control, 57, 992-1003. DOI: 10.1177/00202940241226854.
14. Song, Lifei, Chen, Houjing, Xiong, Wenhao, Zaopeng, Dong, Mao, Puxiu, Xiang, Zuquan, & Hu, Kai. (2019). Collision Avoidance Method for Unmanned Surface Vehicles (USVs) Based on Motion Capability Database. Polish Maritime Research, 26, 55-67. DOI: 10.2478/pomr-2019-0025.
15. Pleskach, Maria. (2016). EvoLogics Explores New Applications for its Sonobot USV: An Unmanned Ground Vehicle for LBL Positioning Aid. Hydro International, 20, 22-25.
16. Peng, Zitian, Yue, Yong, Zhu, Xiaohui, Huang, Mengze, Wong, Pru- dence, Yao, Shanliang, Li, Zhuoxiao, & Hou, Dunkun. (2023). Application of Digital Twins in Unmanned Surface Vehicles: A Review. DOI: 10.1109/CSECS 60003.2023.1042834.
17. Kazaku, Mihai, Axinte, Tiberiu, & Curcea, Elena. (2024). The Importance of Unmanned Surface Vehicles: A Perspective. International Journal of Advanced Multidisciplinary Research, 4. DOI: 10.62225/2583049X.2024. 4.2.2730.
18. Yang, Xiaofei, She, Hongwei, Lu, Mengmeng, Ye, Hui, Guan, Jun, Li, Jianzheng, Xiang, Zhengrong, & Shen, Hao. (2024). Joint Ship Detection and Waterway Segmentation Method for Environmentally Safe Unmanned Vehicles on Canal Waterways. IEEE Transactions on Automation Science and Engineering. DOI: 10.1109/TASE.2024.3375300.
19. Liu, Yuanchang, Song, Rui, Bucknell, Richard, & Zhang, Xinyu. (2019). Intelligent Multi-Task Allocation and Planning for Multiple Unmanned Surface Vehicles (USVs) Using Self-Organizing Maps and Fast Marching Method. Information Sciences, 496. DOI: 10.1016/j.ins.2019.05.029.
20. Santos, Mateus, Bartlett, Ben, Schneider, Vincent, Braday, Fiacra, Blank, Benjamin, Santos, Philip, Trslik, Petar, Riordan, James, & Dooley, Gerard. (2024). Cooperative Unmanned Aerial and Surface Vehicles for Extended Coverage in Marine Environments. IEEE Access. DOI: 10.1109/ACCESS. 2024.3353046.
21. Wang, Liqian, Dong, Yakui, Fei, Chen, Liu, Junlian, Fan, Shuzhen, Liu, Yongxia, Yongfu, Li, Liu, Zhao, & Xiang. (2024). Lightweight SNN for Multisource Infrared Ship Detection from Unmanned Marine Vehicles. Heliyon, 10, e26229. DOI: 10.1016/j.heliyon.2024.e26229.
22. Xu, Hu, Zhang, Xiaomin, He, Ju, Pan, Changsong, & Yu, Yang. (2024). ROTracker: A Novel Radar-Based Object Tracking Method for Unmanned Surface Vehicles in Marine Environments. Frontiers in Marine Science, 11. DOI: 10.3389/fmars.2024.1411920.
23. Kang, Zheng, Gao, Miao, Liao, Zihao, & Zhang, Anmin. (2024). Joint Ocean Observation Research Based on Communication with Heterogeneous Unmanned Surface Vehicles. Frontiers in Marine Science, 11. DOI: 10.3389/fmars.2024.1388617.
24. Chong, Sang, Kim, Min, Park, He, Kim, Yoon, & Ji, De Hyeong. (2024). Fault Diagnosis Technology for Efficient Swarm Management of Unmanned Surface Vehicles. Applied Sciences, 14, 4210. DOI: 10.3390/app14104210.
25. Zhang, Zheng, Huang, Bin, Zhou, Bin, & Miao, Jianming. (2024). Anti- Crowding Interaction Mechanism Based on Leaderless Formation Control for Unmanned Surface Vehicles with Intermittent Communication. IEEE Transactions on Vehicle Technology. DOI: 10.1109/TVT.2024.3423478.
26. Melnyk O., Onyshchenko S., Koskina Y., Aleksandrovska N., Drozhzhyn O., Maluha E., Pulyaev I., Bondaryuk M. (2024). Full overlap ship security model: an integrative approach to shipboard equipment information security. E3S Web of Conferences, 501, art. no. 02002. DOI: 10.1051/e3sconf/202450 102002
27. Korban D., Melnyk O., Onishchenko O., Kurdiuk S., Shevchenko V., Obniavko T. (2024). Radar-based detection and recognition methodology of autonomous surface vehicles in challenging marine environment. Scientific Journal of Silesian University of Technology. Series Transport, 122, pp. 111 – 127. DOI: 10.20858/sjsutst.2024.122.7
28. Melnyk O., Onishchenko O., Onyshchenko S., Voloshyn A., Kalinichenko Y., Rossomakha O., Naleva G., Rossomakha O. (2022). Autonomous Ships Concept and Mathematical Models Application in their Steering Process Control. TransNav, 16 (3), pp. 553-559. DOI: 10.12716/1001.16.03.18