Unmanned surface vehicle energy consumption modelling under various realistic disturbances integrated into simulation environment

Energy consumption estimation and management of the maritime Unmanned Surface Vehicles (USV) is an important issue to deal with energy minimization techniques such as path planning, tasks scheduling, etc. In this paper, the authors introduce the energy consumption parameter in USV simulation through three contributions: 1) An analytic USV's energy consumption model is developed based on the three-degrees-of-freedom dynamic model of surface vessels. 2) A reverse engineering approach is proposed to identify the previously used dynamic model parameters based on a set of scenarios executed within a recent simulation environment. 3) The simulator engine is enriched with the consumption modelling tools such that the power absorbed by the USV is instantaneously calculated and returned; thus, the required energy of any predefined scenario is available as a new simulation result.

• Record URL:
  • https://doi.org/10.1016/j.oceaneng.2020.108560
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0029801820314682
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00298018
• Supplemental Notes:
  • © 2020 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Touzout, Walid
  • Benmoussa, Yahia
  • Benazzouz, Djamel
  • Moreac, Erwan
  • Diguet, Jean-Philippe
• Publication Date: 2021-2-15

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Serial:
  • Ocean Engineering
  • Volume: 222
  • Issue Number: 0
  • Publisher: Pergamon
  • ISSN: 0029-8018
  • EISSN: 1873-5258
  • Serial URL: http://www.sciencedirect.com/science/journal/00298018

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Dynamic models; Energy consumption; Robots; Ships; Simulation
• Subject Areas: Energy; Marine Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01765288
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 22 2021 10:20AM