基于大数据技术的船舶油耗监测系统设计

为适应IMO关于船舶记录油耗数据的强制性要求,分析船舶油-机-环境系统的监测参数集,建立基于大数据技术的、具备船舶油耗数据分析能力的船舶油耗监测系统,使该系统可对船舶油耗信息进行收集、整合和挖掘,向有关部门提供优质的船舶油耗监测服务和实时的节能管理咨询服务。利用无线传感器采集数据监测船舶能耗并开发船舶能耗数据库,不仅为船舶运营管理提供参考依据,还有助于船舶所有人更直观地掌握船舶实时动态信息,更方便地调度和管理船舶。     

基于人工神经网络的船舶油耗模型

针对船舶能效管理计划SEEMP的实施需求,寻求建立油耗模型的通用方法,为航行优化提供决策基础。以丹麦籍客滚轮MS Smyril号作为研究案例,对船舶实测运行数据进行了分析和预处理,并采用人工神经网络构建了船舶油耗和航速的黑箱模型。基于实测数据与模型预测数据的对比,验证了上述油耗模型的准确性和实用性,对于提高船舶能效运行指数EEOI具有重要意义。     

船舶主要动力设备能效模型与仿真分析

根据船、机、桨关系,以船舶动力装置的能量传递为基础,基于Matlab/Simulink仿真平台建立主机能效模型。以某内河旅游船舶为研究对象,根据船体与主机参数,利用回归多项式法得到螺旋桨敞水特性曲线。在船舶上安装油耗仪等传感器,采集了主机瞬时油耗、船舶对地航速、对水航速等数据,并计算了主机的实际能效。针对实船采集的数据,分析了航道水流速度的分布特征。基于仿真模型,计算了船舶在不同航道水流速度与对水航速下的主机能效,比较分析了实测数据与仿真结果,并对模型进行了验证。本文研究对于提升船舶的营运能效指数具有实际指导意义。     

基于航行数据的船舶航行油耗模型建立方法

准确评估船舶的能效表现是研究船舶性能、优化船舶能效的基础。为准确评估船舶航行状态对船舶航行油耗的影响和船舶的能效表现,以某超大型散货船为研究对象,基于船舶智能能效综合管理系统获取大量船舶航行数据,通过数据处理和特征工程找出影响船舶航行油耗的因素,采用人工神经网络建立船舶航行油耗模型。采用该模型预估船舶在一段航程中的总油耗量,验证该模型在评估船舶航行状态对船舶航行油耗的影响方面的有效性。此外,采用该模型对航程和转速进行优化,验证该模型对能效优化的可行性。     

基于数据驱动的船舶油耗预测模型研究

以某客滚船为研究对象,将大量航行实际数据进行预处理,通过斯皮尔曼等级相关分析选择出船舶左右桨螺距、左右舷舵角、纵倾、船首风速、船舶对水和对地航速为油耗主要影响参数。建立基于LSTM神经网络的黑箱模型对数据进行学习并预测油耗,额外选取测试样本验证模型精度,优化模型内部结构以进一步提高预测精度。将最终得到的预测数据与实测数据对比,证明模型具有良好的准确性。该研究方法能为船舶运营人员优化运营方案提供参考,能够提高水路交通运输的经济性。     

某2400 TEU集装箱姊妹船能效分析

为了更好地对船舶营运性能进行管理和评估,研究了2艘2400 TEU集装箱船,并对其船速、主机功率和主机转速等参数以及船舶油耗进行分析对比,运用数据可视化和机器学习等大数据分析方法,实现对船舶能效数据的可视化,通过对比分析得出影响船舶转速与功率的主要因素.     

基于船舶日志的船舶主机碳排放核查

船舶碳排放核查是航运碳减排的基础工作。船舶主机作为主要的碳排放源，是船舶碳排放核查的重中之重。根据国际公约的要求，为核查评估船舶记录的主机碳排放数据，通过研究主机、螺旋桨的功率、转速相关特性，基于航海日志和轮机日志等船舶日志记录的船舶营运参数，提出估算船舶主机油耗量等碳排放数据的方法，并考虑多种因素将估算值相对记录值的绝对偏差设定在5%以内，以评估船舶日志记录的主机碳排放数据的合理性。该方法简单易行，可方便主机碳排放数据的核查评估，供相关方参考。     

基于GPRS船舶燃油监控管理系统的研制

为了满足船舶油耗状况参数的采集与处理分析,本文对基于GPRS移动网络、组态软件的网桥通信实现方法,及API应用程序接口进行了研究,应用GPRS技术、组态软件和智能传感器,研制了B／S架构的船舶燃油监控管理系统,并进行了实船试验。     

基于BP神经网络的船舶主机能效状态评估

[目的]在船舶航行期间,需要通过分析船舶和主机的运行参数来客观判断主机当前的工作情况,从而准确评估主机的能效状态。[方法]以状态良好的船舶运行记录为样本,结合主成分分析法和BP神经网络算法,构建船舶的航行状态识别模型和主机油耗模型,并在船舶航行期间对船舶实时运行参数进行分析,得出船舶主机在当前工况下的油耗量正常值。以某30万吨级远洋散货船为例开展模型计算验证,将正常油耗值与实际油耗值进行对比,以二者的残差值为依据,进而评估当前的主机能效状态。[结果]计算结果显示,航行状态识别模型的正确率为98.05%,油耗模型的平均误差为3.47%,2种模型的可靠性均较高。[结论]研究成果可为智能船舶的能效管理提供一定的参考。     

基于数据驱动的船舶航线实时优化

为了给不同海况下的船舶安全航行提供保障,设计基于数据驱动的船舶航线实时优化方法。利用数据驱动方法采集船舶历史航线、海域风速、风向、波高等海况数据,选取K-means聚类算法聚类海况数据,构建海况知识库。依据海况知识库内的船舶航线信息与航线转向点信息,划分船舶航线为不同航段。依据船舶航线的航段划分结果,以航行总时间最短以及总油耗最低为目标函数,设置船舶航速约束与转向点位置约束作为约束条件,构建航线实时优化模型。选取蚁群算法求解所构建的优化模型,输出航线实时优化结果。结果表明,该方法可以实时优化航线,降低船舶的航行时间与主机油耗,适用于不同海况的船舶航行。     

Voyage-based statistical fuel consumption models of ocean-going container ships in Korea

ABSTRACT

Accurately estimating fuel consumption of ships is crucial for shipping companies, port authorities, and environmental protection agencies. The bottom-up approach is becoming increasingly popular because it can estimate ship fuel consumption by accounting for ship activity conditions, such as changes in voyage speed, time, and distance; however, its use is still limited when estimating ship fuel consumption. Ship-specific information, such as the daily fuel consumption rate for main and auxiliary engines for every vessel, is expensive to gather, and generally not collected from private shipping companies. To address this research gap, we develop simplified and composite ship fuel consumption models for ocean-going container ships by size using a regression model. To estimate the fuel consumption models for container ships, we rely on ship activity data, including average speed and sailing time, distance, and actual fuel consumption for main and auxiliary engines. This information is obtained from a major container shipping company in Korea. We estimate and validate the parameters associated with fuel consumption for five different container ship sizes, all of which are smaller than the Post-Panamax container ship (15,000 TEU and above).     

The influence of route choice and operating conditions on fuel consumption and CO<Subscript>2</Subscript> emission of ships

The influence of various parameters, such as ship initial speed (full ahead and lower engine loads), loading condition, heading angle and weather conditions on ship fuel consumption and CO₂ emission is presented. A reliable methodology for estimating the attainable ship speed, fuel consumption and CO₂ emission in different sea states is described. The speed loss is calculated by taking into account the engine and propeller performance in actual seas as well as the mass inertia of the ship. The attainable ship speed is obtained as time series. Correlation of speed loss with sea states allows predictions of propulsive performance in actual seas. If the computation is used for weather routing purposes, values for various ship initial speed, loading conditions and heading angles for each realistic sea‐state must be provided. The voluntary speed loss is taken into account. The influence of the ship speed loss on various parameters such as fuel consumption and CO₂ emissions is presented. To illustrate the presented concept, the ship speed and CO₂ emissions in various routes of the Atlantic Ocean are calculated using representative environmental design data for the track of the routes where the ship will sail.     

串联式混合动力内河船舶参数匹配及控制策略研究

以某环境监测船为研究对象,根据基本参数与设计指标,在满足船舶动力性指标要求的前提下对船舶动力系统进行参数匹配,提高船舶经济性并改善排放性能。在混合动力船舶电力推进试验平台上采用切换理论控制策略进行仿真试验,结果表明,船舶在满足性能要求的前提下,燃油消耗量大幅降低,验证了动力系统参数匹配结果及控制策略的合理性和可行性。     

混合动力电动船舶模糊逻辑控制策略

混合动力电动船舶对于纯电动船舶具有较好的续航能力,适用于航线较长且具有随机性的船舶工况,同时对于工程作业船舶工况其可以降低柴油发电机为动力的工程作业船舶柴油机功率,减少燃油消耗与排放。本文分析了上述两种不同船舶工况特点,并针对该工况采用串联式混合动力结构作为船舶动力系统结构并根据工况需求设计了相应的模糊逻辑控制策略。运用MATLAB/Simulink搭建了系统仿真模型,仿真结果表明,所设计串联式混合动力系统及其模糊逻辑控制策略能够在上述两种船舶工况下实现控制要求。     

船舶燃油计算机管理系统的研究

介绍了一种船舶燃油计算机管理系统的有关情况。该系统可以利用现在船上使用的检测报警系统计算机实现船舶燃油管理系统的计算机连续在线自动测量，实现船舶燃油管理中的统计、记录、运算和预测功能。     

船舶中央冷却系统节能优化设计研究

现代船舶设计中,节能设计成为船舶设计成败的关键之一。为了降低船舶的燃油消耗,除通过优化船体线型减小船体阻力、增加桨径提高推进效率外,还可以通过对一些系统进行优化布置来实现一定的节能目的。以一型5万吨级散货系列船为例,利用功能关系转换的方法,通过表列比较其中央冷却系统改进前后对燃油消耗量的变化,证实了改进后的系统对燃油消耗量有所降低,从而说明通过对动力系统优化布置是可以达到一定的节能效果。     

Ship resistance when operating in floating ice floes: Derivation,validation, and application of an empirical equation

With the effects of global warming, the Arctic is presenting a new environment where numerous ice floes are floating on the open sea surface. Whilst this has improved Arctic shipping navigability in an unprecedented way, the interaction of such floes with ships is yet to be understood to aid the designing of ships and route planning for this region. To further explore this topic, the present work develops a procedure to derive an empirical equation that can predict the effects of such floes on ship resistance. Based on a validated computational approach, extensive data are extracted from simulations of three different ships with varying operational and environmental conditions. The ice-floe resistance is shown to strongly correlate with ship beam, ship buttock angle, ship waterline angle, ship speed, ice concentration, ice thickness and floe diameter, and the regression powers of each of the parameters on resistance are ascertained. This leads to a generic empirical equation that can swiftly predict ice-floe resistance for a given ship in a given condition. Subsequently, demonstrations are given on the incorporation of the derived equation into a set of real-time Arctic ship performance model and voyage planning tool, which can predict a ship's fuel consumption in ice-infested seas and dynamically suggest a route with the least safety concern and fuel consumption. Moreover, the equation is validated by providing ice resistance prediction for experimental and full-scale conditions from multiple sources, showing high accuracy. In conclusion, the empirical equation is shown to give valid and rapid estimates for ice-floe resistance, providing valuable insights into ship designs for the region, as well as facilitating practical applications for polar navigation.     

基于ARM和μC/OS-II的船用柴油机最低油耗航速控制系统设计与实现

介绍一种船舶柴油机最低油耗航速控制系统.利用这套系统可以在不影响船舶航行安全和航运周期的前提下,通过实时检测的方式,控制主机运行于最低油耗航速,从而大大降低船舶航行时的主机燃油消耗.