Study On Vessel Fuel Consumption Model

The International Maritime Organization is planning to establish a mandatory standard applying to all operating ships with Ship Energy Efficiency Management Plan(SEEMP) in order to gradually control and reduce CO2 emission from shipping industry. Considering that fuel expense occupies the largest portion among all ship operating costs, this plan will also reduce energy consumption and brings considerable savings in fuel expense in the meantime. These economic, environmental and legal factors codetermine that all ships should be in operation with less fuel consumption and emission in the near future, thus leading to higher demands to ships and crews in technological and managing level.The implementation of SEEMP requires a thorough understanding of all fuel consumption related factors and a model to predict fuel consumption based on such understanding. Against this backdrop, this dissertation is aimed at finding a common approach to establishing a predicting model to quantify the impact of environmental and operational factors towards ship speed and fuel consumption. Such model provides a decision basis for voyage planning and plays a significant role in improving Energy Efficiency Operational Indicator(EEOI) of all ships.In this dissertation, Danish ferry MS Smyril has been taken as a study case for the analysis and preprocessing of its measured data, and a predicting model for ship speed and fuel consumption has been constructed with artificial neural network. From comparison of measured data with model predictions, the accuracy and practicality of the model has been validated, thus offering valuable preference in following studies and applications.