【作者】 张强；

【导师】 孙宝芝；

【作者基本信息】 哈尔滨工程大学 ， 动力工程及工程热物理， 2022， 硕士

【摘要】 船舶远洋运输是国际贸易最主要的运输方式,但航运业每年CO₂排放高达10亿吨,在气候问题愈发引起各国关注,碳达峰、碳中和已成为国际共识的背景下,航运业迫切需要降低碳排放以满足越发严格的法规要求。航速优化因其投资少而收益显著备受船东青睐,而基于船机桨动态特性的航速优化研究,不仅能够通过优化各航段航速降低船舶主机燃油消耗,还可以充分考虑船舶航行动态特性,对于指导船舶经济运行具有非常重要的意义。以某30万吨级远洋油船为研究对象,分析动态过程中各航行参数随航速的变化规律,基于船机桨之间数学物理关系建立动态过程数学与仿真模型。同时基于船舶航行数据建立主机油耗机器学习模型,采用随机搜索与网格搜索相结合的方法进行模型超参数寻优,并模拟实际航行环境评估模型预测可靠性。对航速离散化处理后采用python语言自主开发源程序,应用Gurobi优化求解器求解稳态航速优化问题,并分析航行时间与气象条件对优化节能效果的影响;在此基础上分别采用迭代计算与动态规划的方法进行动态航速优化研究。研究结果表明,所建动态过程仿真模型能够准确捕捉与记录加减速过程中各参数的变化,满足10%左右的工程应用误差;主机油耗预测模型相对误差均在4%以内,模型预测准确性较高。航速优化能够实现较好的节油效果:与历史航行数据相比节油量为45.43 t,节油率可达6.44%;与准时恒速航行相比节油量为26.61 t,节油率为3.88%。由于动态过程主机油耗、航行距离与持续时间在全航程中占比很小（分别为0.378%、0.276%、0.290%）,因此从节油效果来看,稳态与动态航速优化差异并不显著,但是动态航速优化充分展现了船舶实际航行时的加减速过程。基于船机桨动态特性的航速优化突破稳态航速优化中存在的航速阶跃变化的局限,在充分考虑船舶加减速过程的同时为船舶节能减排提供了可行技术手段。更多还原

【Abstract】 Ocean shipping is the most important mode of transportation in international trade,but the annual CO₂ emission of the shipping industry is up to 1 billion tons.Under the background of climate issues attracting more attention from countries around the world and peak carbon dioxide emission and carbon neutrality have become the international consensus,the shipping industry urgently needs to reduce carbon emissions to meet the increasingly strict regulatory requirements.Ship speed optimization is favored by ship owners because of its low investment and significant benefits.The research on ship speed optimization based on the dynamic characteristics of hull-propeller-engine can not only reduce fuel consumption of ship main engine by optimizing the speed of each section,but also fully consider the dynamic characteristics of ship navigation,which is of great significance for guiding the economic operation of ships.In this paper,a 300,000-ton ocean-going tanker is taken as the research object,and the variation law of different parameters with ship speed in the dynamic process is analyzed.The mathematical and simulation model of dynamic process is established based on the mathematical and physical relationship between hull-propeller-engine.The machine learning model of fuel consumption was established based on ship navigation data,and the method of random search and grid search was used to optimize the hyperparameters of the model,and the reliability of model prediction was evaluated by simulating the actual navigation environment.The ship speed is discretized and Python was used to independently develop the source program,and Gurobi optimization solver was used to solve the steady-state ship speed optimization problem,and the effects of sailing time and meteorological conditions on the optimization results were analyzed.On this basis,iterative calculation and dynamic programming are used to study dynamic speed optimization.The results show that the dynamic process simulation model can accurately capture and record the changes of various parameters during acceleration and deceleration,and all of them meet the engineering application error of about 10%.The relative errors of fuel consumption prediction models are all within 4%,which show the prediction accuracy of the models is high.Speed optimization can achieve better fuel saving effect,compared with the historical voyage,the fuel saving is 45.43t and the fuel saving rate can reach 6.44%;compared with the sailing on punctual constant speed,the fuel saving is 26.61t and the fuel saving rate is 3.88%.Since fuel consumption,sailing distance and duration of dynamic process account for a very small proportion in the whole voyage（0.378%,0.276%and 0.290%,respectively）,there is no significant difference between steady-state and dynamic speed optimization in terms of fuel saving effect.But dynamic speed optimization fully demonstrates the acceleration and deceleration process of the ship during actual voyage.The research work in this paper breaks through the limitation of only considering steady-state navigation,and provides feasible technical means for energy conservation and emission reduction of ships while fully considering the dynamic process of ship voyage.更多还原