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基于模型预测控制的混合动力船舶能量管理系统在各种海况下的优化设计

Optimal design of a hybrid ship energy management system under various sea conditions using Model Predictive Control.

作者信息

Mushtaq Rafia, Iqbal Muhammad, Khaliq Abdul, Iqbal Jamshed

机构信息

Department of Electrical and Computer Engineering, Sir Syed CASE Institute of Technology, Islamabad, Pakistan.

Department of Computer Science, National University of Technology (NUTECH), Islamabad, Pakistan.

出版信息

PLoS One. 2025 Jul 2;20(7):e0326969. doi: 10.1371/journal.pone.0326969. eCollection 2025.

DOI:10.1371/journal.pone.0326969
PMID:40601606
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12221062/
Abstract

This paper introduces an optimal design and control approach for a hybrid ship energy management system under various sea conditions by employing model predictive control. Ship reliability and environmental sustainability can be enhanced by reducing emissions and ecological impact. When a ship navigates, it encounters varying sea conditions, and as a result, the ship's generator can experience substantial loading stress due to power fluctuations, particularly in unfavorable conditions. These fluctuations can disrupt the generator or even cause it to fail to supply the necessary power to the ship. A model predictive control (MPC) law has been devised to effectively manage the hybrid energy storage system of batteries and supercapacitors, dynamically responding to power variations induced by ocean waves. This study investigates the performance characteristics of the energy storage system across various battery weight configurations (1,5,10,20,30,50). We explore different weightings of batteries and supercapacitors to analyze their impact on system behavior. The numbers related to the battery weight configurations represent different configurations or setups of the hybrid energy storage system within the ship. The significance of these numbers lies in their impact on the performance of the energy management system and consequently, the overall operation of the vessel. By exploring various battery weight configurations, the study aims to understand how different setups affect the behavior and effectiveness of the hybrid energy storage system. The effectiveness of the proposed methodology is demonstrated through MATLAB simulations under varying sea conditions, including light, moderate, and heavy, successfully mitigating power variations and averting generator failure. Interestingly, the findings reveal that saturation occurs in their respective currents when the weightage difference among these energy storage components surpasses 20.

摘要

本文介绍了一种采用模型预测控制的混合船舶能量管理系统在各种海况下的优化设计与控制方法。通过减少排放和生态影响，可以提高船舶的可靠性和环境可持续性。船舶航行时会遇到不同的海况，因此，船舶发电机可能会因功率波动而承受巨大的负载压力，尤其是在不利条件下。这些波动可能会扰乱发电机，甚至导致其无法为船舶提供所需的电力。已设计出一种模型预测控制（MPC）定律，以有效管理电池和超级电容器的混合储能系统，动态响应海浪引起的功率变化。本研究调查了不同电池重量配置（1、5、10、20、30、50）下储能系统的性能特征。我们探索了电池和超级电容器的不同权重，以分析它们对系统行为的影响。与电池重量配置相关的数字代表船舶内混合储能系统的不同配置或设置。这些数字的重要性在于它们对能量管理系统性能的影响，进而对船舶的整体运行产生影响。通过探索各种电池重量配置，该研究旨在了解不同设置如何影响混合储能系统的行为和有效性。通过在包括轻载、中载和重载在内的不同海况下进行MATLAB仿真，证明了所提出方法的有效性，成功减轻了功率变化并避免了发电机故障。有趣的是，研究结果表明，当这些储能组件之间的权重差异超过20时，它们各自的电流会出现饱和。

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