Systems and methods for optimizing vessel fuel consumption

A system for determining an optimum engine configuration for a seafaring vessel having a plurality of thrust engines, the system comprising:

• a plurality of sensors positioned onboard the vessel;
• at least one processor;
• and
• at least one data storage unit storing a required power model and a plurality of fuel consumption models corresponding to the plurality of thrust engines, wherein the required power model is a first machine learning model trained to determine a predicted required power, and wherein each fuel consumption model includes a machine learning model configured to receive a power output level for the corresponding thrust engine as an input and to generate an engine-specific predicted fuel consumption by the corresponding thrust engine as an output;
• wherein the at least one processor is configured to:
• receive vessel operational data and environmental data for a desired voyage, wherein at least some of the vessel operational data and environmental data is received from the plurality of sensors;
• determine the predicted required power by inputting the vessel operational data, the environmental data, and voyage data to the required power model, wherein the voyage data defines at least one characteristic of the desired voyage;
• and
• determine an optimum engine configuration based on the predicted required power, wherein the optimum engine configuration is selected from a plurality of candidate engine configurations, wherein each candidate engine configuration includes a specified number of thrust engines running and a specified power output level of each thrust engine, and for each candidate engine configuration, a sum of power output from each of the thrust engines is at least equal to the predicted required power, wherein the optimum engine configuration is selected by:
• for each candidate engine configuration, determining a candidate total predicted fuel consumption amount by:
• for each thrust engine running in that candidate engine configuration, determining an engine-specific predicted fuel consumption using the engine-specific fuel consumption model defined for that thrust engine;
• and
• determining the candidate total predicted fuel consumption amount as a sum of the engine-specific predicted fuel consumption determined for each running thrust engine;
• and
• selecting the optimum engine configuration from the candidate engine configurations based on the candidate total predicted fuel consumption of each candidate engine configuration.

A computer program product comprising a non-transitory computer readable medium storing computer executable instructions for configuring a processor to perform a method for determining an optimum engine configuration for a seafaring vessel having a plurality of thrust engines, wherein the method comprises:

• receiving vessel operational data and environmental data for a desired voyage, wherein at least some of the vessel operational data and environmental data is received from a plurality of sensors positioned onboard the vessel;
• determining a predicted required power by inputting the vessel operational data, the environmental data, and voyage data to a required power model, wherein the required power model is a first machine learning model trained to generate the predicted required power as an output, and the voyage data defines at least one characteristic of the desired voyage;
• and
• determining an optimum engine configuration based on the predicted required power, wherein the optimum engine configuration is selected from a plurality of candidate engine configurations, wherein each candidate engine configuration includes a specified number of thrust engines running and a specified power output level of each thrust engine, and for each candidate engine configuration, a sum of power output from each of the thrust engines is at least equal to the predicted required power, wherein the optimum engine configuration is selected by:
• for each candidate engine configuration, determining a candidate total predicted fuel consumption amount by:
• for each thrust engine running in that candidate engine configuration, determining an engine-specific predicted fuel consumption using an engine-specific fuel consumption model defined for that thrust engine, wherein each fuel consumption model includes a machine learning model configured to receive a power output level for the corresponding thrust engine as an input and to generate the engine-specific predicted fuel consumption by the corresponding thrust engine as an output;
• and
• determining the candidate total predicted fuel consumption amount as a sum of the engine-specific predicted fuel consumption determined for each running thrust engine;
• and
• selecting the optimum engine configuration from the candidate engine configurations based on the candidate total predicted fuel consumption of each candidate engine configuration.