Model Predictive Control for the Reduction of Marine Propellers Vibrations

Constanza Ahumada, Luca Tarisciotti, Diego Sepúlveda, Doris Sáez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In recent years, hybrid marine vessels are gaining importance for their capability of reducing CO2 emissions. In these vessels, the use of electric propulsion, in which the electrical energy is provided through an electric grid, allows 35% of fuel savings. However, to reduce the weight of the propulsion system, the shaft connections in the overall system are often very flexible, allowing vibrations to be excited. Torsional vibrations can be excited by sea perturbations such as ventilation, damaging the propeller or reducing its life. This paper studies the excitation of torsional vibrations and proposes a Model Predictive Control (MPC) strategy to reduce them. For this, a simplified model of marine vessel propellers is considered and the MPC strategy is applied and analysed for different sources of vibrations. The proposed strategy is also analysed under different uncertainty scenarios and for different input variables. The results show that the proposed MPC reduces the torsional vibrations while maintaining the same speed control characteristics.

Original languageEnglish
Title of host publication2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728193878
DOIs
Publication statusPublished - 2022
Event2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 - Detroit, United States
Duration: 9 Oct 202213 Oct 2022

Publication series

Name2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022

Conference

Conference2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
Country/TerritoryUnited States
CityDetroit
Period9/10/2213/10/22

Keywords

  • Marine Propulsor
  • Model Predictive Control
  • Predictive Control
  • Vibrations

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

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