基于多环反馈的混合动力系统正向仿真与策略应用

Forward simulation and strategy application of hybrid power system based on multi-loop feedback

  • 摘要: 【目的】船舶混合动力系统日趋复杂,对系统性建模提出了更高要求。【方法】以长江内河7500吨散货船为研究对象,分析其动力系统拓扑结构和工作模式,提出基于多环反馈的正向机理建模方法,采用Simulink构建船舶柴气电混合动力系统模型,并设计规则型能量管理策略与功率控制器。最后基于实测数据,从油耗、转速控制响应、充放电特性、发电特性和船机桨匹配等方面对模型适用性展开分析;通过对比既有功率流和AMESIM模型,分析本模型在策略应用的潜在价值。【结果】结果表明,该模型具有良好的转速及功率响应特性,四种模式下船机桨匹配特性与目标船趋于一致,可在<4 %的误差范围内模拟目标船动态特性,能够有效体现中间环节损失、控制响应、模式切换和变流器干扰等因素对能量管理过程的影响,在0.001 s步长下通过dSPACE实时仿真测试,具有良好的实时性能。【结论】可为多能源混合动力系统能量管理长时域、全工况测试提供实时模型支持。

     

    Abstract: Objectives With the escalating complexity of the Marine hybrid power system, more rigorous requirements are imposed for systematic modeling. Methods This study focuses on a 7,500-ton bulk carrier operating on the Yangtze River, analyzing the topology and operating modes of its power system. A forward mechanism modeling approach based on multi-loop feedback is proposed, and a hybrid diesel-gas-electric power system model is developed using Simulink. A rule-based energy management strategy and power controller are designed to optimize system performance. Finally, the model's applicability is analyzed using measured data, considering fuel consumption, speed control response, charge-discharge characteristics, power generation features, and the matching between the ship, engine, and propeller. Comparative analyses with existing power flow and AMESIM models highlight the potential value of this model for energy management strategy applications. Results The results demonstrate that the model exhibits excellent speed and power response characteristics. The ship-engine-propeller matching characteristics across four operating modes align closely with those of the target vessel, achieving dynamic simulations within a margin of error of less than 4%. The model effectively captures the impacts of intermediate losses, control responses, mode transitions, and converter disturbances on the energy management process. Furthermore, it was validated through dSPACE real-time simulation tests with a 0.001 s step size, showcasing strong real-time performance. Conclusions It provides real-time model support for long-duration and full-operating-condition testing of multi-energy hybrid system energy management.

     

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