ObjectiveIn order to improve the energy efficiency of ships, this paper studies the energy efficiency optimization method of fuel cell/lithium battery hybrid ships under the influence of multiple factors. MethodBased on MATLAB/Simulink simulation modeling software, simulation models of the fuel cell, lithium battery, DC-DC converter, ship hydrostatic resistance, ship navigation environmental resistance, ship motion and ship propeller are built respectively. On this basis, an energy efficiency simulation model of the target ship is established, and the influence of navigational elements such as wind speed, wind direction, water depth and wave height on the energy efficiency of the ship is studied. Aiming at the target ship's hybrid system structure, a power allocation strategy based on fuzzy logic is used to optimize the system's energy flow. Taking the minimum total energy consumption of the system as the optimization goal and considering multiple internal and external constraints, a non-linear model of ship speed optimization in light of multiple factors is established. The intelligent optimization algorithm of the whale population is used to carry out the dynamic optimization of the non-linear ship speed model, and a comparative analysis of energy efficiency optimization under different navigation methods is performed. ResultsThe results show that under the condition that the total voyage time remains unchanged, the proposed multi-factor optimization method of ship energy efficiency can reduce total energy consumption by 5.04% and total hydrogen fuel cell consumption by 13.16%. ConclusionThe proposed method has a positive effect on ship energy conservation and emission reduction, giving it great significance for improving the endurance and economy of ships.


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    Title :

    Energy efficiency optimization analysis of fuel cell/lithium battery hybrid ship based on whale optimization algorithm


    Contributors:
    Dongliang HU (author) / Yupeng YUAN (author) / Xiaohao QU (author) / Qizhi YIN (author)


    Publication date :

    2022




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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