Ship navigational speed optimization auxiliary decision-making system

Abstract

A ship navigational speed optimization auxiliary decision-making system comprises a weather forecast analyzer, an oil consumption prediction model, an ocean route reconstruction model, a genetic algorithm solver, a data acquisition platform and a ship end interface, wherein the data acquisition platform and the ship end interface are arranged at a ship end, and the oil consumption prediction modelis used for predicting the fuel consumption per hour of a main engine under an actual sea condition; the ocean route reconstruction model is used for carrying out equidistant segmentation on the route of a target ship and re-planning the remaining routes according to the current position of the target ship; the genetic algorithm solver is used for calculating the optimal rotating speed solution of the minimum fuel consumption of an airline; and the ship end interface is used for inputting predefined route information and displaying route and navigational speed optimization suggestions. The ship navigational speed optimization auxiliary decision-making system has the advantages that the oil consumption per hour estimation model and the navigational speed optimization model of the main engine containing stormy wave factors of a specific ship are established according to test data, and the optimal energy-saving navigation state adapting to the ship navigation environment and the runningrotating speed of the main engine of each navigation segment are given through a full-voyage navigation speed optimization decision by taking the minimization of voyage fuel consumption as a target, so that the ship safety and energy conservation are realized.

Description

technical field [0001] The invention relates to the technical field of ship route speed optimization, in particular to an auxiliary decision-making system for ship speed optimization. Background technique [0002] The optimization of ship sailing speed plays an important role in reducing fuel costs and greenhouse gas emissions. Cost control is a necessary means for many shipping logistics companies to survive in the fierce market competition. Mainly since 2008, the international maritime logistics market is still affected by the 2008 financial crisis. Many researchers use different technological innovations to help companies save costs, including speed optimization. For many maritime logistics companies such as Maersk, finding the optimal speed solution with the lowest fuel consumption is a cost control solution. In addition, speed optimization helps reduce greenhouse gas emissions. According to the United Nations report, maritime logistics accounts for more than 70% of ...

AI Technical Summary

Problems solved by technology

[0006] 1. Problems existing in the research of the engine fuel consumption prediction model per hour

[0007] ①There is a lack of basic performance data of the target ship as a calculation support. Many fuel consumption estimation models are based on empirical formulas or data collected from similar ships, and empirical formulas are not applicable for different ship characteristics.

[0008] ② Lack of calculating the impact of meteorological factors

[0009] ③Lack of real ship data to correct basic performance data

[0010] ④ It is difficult to guarantee the prediction accuracy of fuel consumption per hour for a specific ship type sailing in a specific weather

[0011] ⑤Seldom consider the relationship between the main engine fuel consumption rate and power

[0013] ① Lack of accurate weather forecast

[0014] ② Lack of dynamic speed optimization function

[0016] ① The speed difference of the main engine between the various turning points of the route is too large

[0017] ② Failure to consider the actual sailing habits of the crew

[0018] ③The optimization algorithm may cause the result of the search to fall into a local optimum, rather than the optimal condition of the entire route. For the defects of the prior art, the present invention is proposed

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