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Control and Optimization of Electric Ship Propulsion Systems with Hybrid Energy Storage

机译：具有混合储能的电动船舶推进系统的控制与优化

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摘要

Electric ships experience large propulsion-load fluctuations on their drive shaft due to encountered waves and the rotational motion of the propeller, affecting the reliability of the shipboard power network and causing wear and tear. This dissertation explores new solutions to address these fluctuations by integrating a hybrid energy storage system (HESS) and developing energy management strategies (EMS). Advanced electric propulsion drive concepts are developed to improve energy efficiency, performance and system reliability by integrating HESS, developing advanced control solutions and system integration strategies, and creating tools (including models and testbed) for design and optimization of hybrid electric drive systems.;A ship dynamics model which captures the underlying physical behavior of the electric ship propulsion system is developed to support control development and system optimization. To evaluate the effectiveness of the proposed control approaches, a state-of-the-art testbed has been constructed which includes a system controller, Li-Ion battery and ultra-capacitor (UC) modules, a high-speed flywheel, electric motors with their power electronic drives, DC/DC converters, and rectifiers.;The feasibility and effectiveness of HESS are investigated and analyzed. Two different HESS configurations, namely battery/UC (B/UC) and battery/flywheel (B/FW), are studied and analyzed to provide insights into the advantages and limitations of each configuration. Battery usage, loss analysis, and sensitivity to battery aging are also analyzed for each configuration. In order to enable real-time application and achieve desired performance, a model predictive control (MPC) approach is developed, where a state of charge (SOC) reference of flywheel for B/FW or UC for B/UC is used to address the limitations imposed by short predictive horizons, because the benefits of flywheel and UC working around high-efficiency range are ignored by short predictive horizons. Given the multi-frequency characteristics of load fluctuations, a filter-based control strategy is developed to illustrate the importance of the coordination within the HESS. Without proper control strategies, the HESS solution could be worse than a single energy storage system solution.;The proposed HESS, when introduced into an existing shipboard electrical propulsion system, will interact with the power generation systems. A model-based analysis is performed to evaluate the interactions of the multiple power sources when a hybrid energy storage system is introduced. The study has revealed undesirable interactions when the controls are not coordinated properly, and leads to the conclusion that a proper EMS is needed.;Knowledge of the propulsion-load torque is essential for the proposed system-level EMS, but this load torque is immeasurable in most marine applications. To address this issue, a model-based approach is developed so that load torque estimation and prediction can be incorporated into the MPC. In order to evaluate the effectiveness of the proposed approach, an input observer with linear prediction is developed as an alternative approach to obtain the load estimation and prediction. Comparative studies are performed to illustrate the importance of load torque estimation and prediction, and demonstrate the effectiveness of the proposed approach in terms of improved efficiency, enhanced reliability, and reduced wear and tear.;Finally, the real-time MPC algorithm has been implemented on a physical testbed. Three different efforts have been made to enable real-time implementation: a specially tailored problem formulation, an efficient optimization algorithm and a multi-core hardware implementation. Compared to the filter-based strategy, the proposed real-time MPC achieves superior performance, in terms of the enhanced system reliability, improved HESS efficiency, and extended battery life.
机译：由于遇到的波浪和螺旋桨的旋转运动，电动船的驱动轴上会有很大的推进载荷波动，从而影响船上电网的可靠性并造成磨损。本文通过整合混合储能系统（HESS）和制定能源管理策略（EMS），探索了解决这些波动的新方法。通过集成HESS，开发高级控制解决方案和系统集成策略以及创建用于设计和优化混合动力驱动系统的工具（包括模型和试验台），开发了先进的电力推进驱动概念来提高能源效率，性能和系统可靠性。开发了捕获电动船舶推进系统基本物理行为的船舶动力学模型，以支持控制开发和系统优化。为了评估所提出的控制方法的有效性，已构建了一个最新的试验台，其中包括系统控制器，锂离子电池和超级电容器（UC）模块，高速飞轮，带有它们的功率电子驱动器，DC / DC转换器和整流器。;对HESS的可行性和有效性进行了研究和分析。研究和分析了两种不同的HESS配置，即电池/ UC（B / UC）和电池/飞轮（B / FW），以深入了解每种配置的优点和局限性。还会针对每种配置分析电池使用情况，损耗分析和对电池老化的敏感性。为了实现实时应用并获得所需的性能，开发了一种模型预测控制（MPC）方法，其中飞轮B / FW的充电状态（SOC）参考或B / UC的UC用于解决该问题。短期预测范围会带来局限性，因为飞轮和UC在高效范围内工作的好处被短期预测范围所忽略。给定负载波动的多频特性，开发了基于滤波器的控制策略来说明HESS内协调的重要性。如果没有适当的控制策略，HESS解决方案可能会比单一储能系统解决方案更差。；所提出的HESS在引入现有船载电力推进系统时将与发电系统相互作用。当引入混合储能系统时，将执行基于模型的分析以评估多个电源的相互作用。这项研究揭示了当控制不正确协调时的不良相互作用，并得出结论，需要适当的EMS 。；对推进负载扭矩的知识对于建议的系统级EMS是必不可少的，但是这种负载扭矩是无法测量的在大多数海洋应用中。为了解决这个问题，开发了一种基于模型的方法，以便可以将负载转矩估计和预测合并到MPC中。为了评估所提出方法的有效性，开发了具有线性预测的输入观察器作为获取负荷估计和预测的替代方法。进行了比较研究以说明负载扭矩估计和预测的重要性，并从提高效率，增强可靠性和减少磨损的角度证明了该方法的有效性。最后，实现了实时MPC算法在物理测试台上。为了实现实时实施，我们进行了三项不同的努力：特制的问题表述，高效的优化算法和多核硬件实施。与基于过滤器的策略相比，提出的实时MPC在增强的系统可靠性，提高的HESS效率和延长的电池寿命方面实现了卓越的性能。

著录项

  • 作者

    Hou, Jun.;

  • 作者单位

    University of Michigan.;

  • 授予单位 University of Michigan.;
  • 学科 Electrical engineering.;Ocean engineering.;Alternative Energy.;Energy.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 177 p.
  • 总页数 177
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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