Application of Sensor Fusion to Drive Vessel Performance

Angelos Ikonomakis, Roberto Galeazzi, Jesper Dietz, Klaus Kähler Holst, Ulrik Dam Nielsen

    Research output: Contribution to conferencePaperResearchpeer-review

    356 Downloads (Pure)

    Abstract

    Typically, slow steaming is adopted to lower ship’s resistance, which in turn reduces exhaust gas emissions due to lower propulsion power demands. Fine tuning of the underlying hydrodynamic models is key to the reliable forecasting of fuel consumption. Accurate knowledge of the vessel’s speedthrough- water (STW) is paramount to estimate the actual resistance of the vessel. The paper presents a feasibility study about the use of sensor fusion methods for real-time estimation of STW based on inertial measurements of ship motions and measurement of sea current. By combining a purely kinematic model together with linear Kalman filtering, the paper addresses the challenge of designing an optimal STW estimator by detailing the fundamental design choices. The proposed STW estimator is verified on simulated data and tested with measured data from an in-service container vessel.
    Original languageEnglish
    Publication date2019
    Publication statusPublished - 2019
    Event4th Hull Performance & Insight Conference (HullPIC’19) - Gubbio, Italy
    Duration: 6 May 20198 May 2019

    Conference

    Conference4th Hull Performance & Insight Conference (HullPIC’19)
    Country/TerritoryItaly
    CityGubbio
    Period06/05/201908/05/2019

    Fingerprint

    Dive into the research topics of 'Application of Sensor Fusion to Drive Vessel Performance'. Together they form a unique fingerprint.

    Cite this