Energy consumption

Fuel efficiency

Quantum mechanics

Control (management)

Engineering

Propulsion

Efficient energy use

Trim

Aerospace engineering

Statistics

Marine engineering

Energy (signal processing)

Operating system

Joint (building)

Power (physics)

Computer science

Physics

Propeller

Mathematics

Automotive engineering

Artificial intelligence

Structural engineering

Artificial neural network

Electrical engineering

Transportation Research Part D Transport and Environment

Operational optimisation is one of the most important methods for reducing energy consumption and emissions related to ships. In this study, a speed-trim joint optimisation method is proposed. First, the propulsion power for various operating conditions was estimated by numerical simulation, two-dimensional method, and ship-engine-propeller principle. Second, the obtained data, consisting of ship power, draft, trim angle, and speed, were further expanded to form a joint optimisation decision database using the artificial neural network method. Subsequently, a dynamic programming algorithm was used to calculate the optimal speed for each segment of the voyage. The optimal trim angle corresponding to the speed was obtained based on the joint optimisation decision database. Finally, a 7500 ton inland bulk carrier was chosen as the case ship to validate the proposed method. The results showed that the method could reduce the total ship power consumption by up to 7.64%.

Joint optimisation for improving ship energy efficiency considering speed and trim control