基于粒子群优化阈值的多堆燃料电池系统功率分配策略研究

Study on power distribution strategy of multi-stack fuel cell system based on particle swarm optimization threshold

  • 摘要:
      目的  为提高混合动力船舶的系统稳定性和效率,提出一种基于粒子群优化阈值的多堆燃料电池系统功率分配策略。
      方法  针对多堆燃料电池和蓄电池并联构成的混合动力源系统,设计基于粒子群优化算法(PSO)的模糊逻辑能量管理策略。根据推进系统负载功率和蓄电池荷电状态(SOC),灵活调控燃料电池单体工作组数及其输出功率,并采用PSO来优化系统的控制阈值。
      结果  Matlab/Simulink仿真结果表明:该能量管理策略可以迅速满足复杂多变的负载功率需求,从而提高混合动力源的系统效率;相较于传统的能量管理策略,基于模糊逻辑和基于粒子群优化阈值的能量管理策略的氢气消耗量分别下降了18.96%和31.48%。
      结论  该智能能量管理策略适用于混合动力船舶多堆燃料电池,可有效提高混合动力源的系统效率并降低氢气消耗量。

     

    Abstract:
      Objectives  To improve the stability and efficiency of hybrid propulsion systems for ships, a power distribution strategy based on the particle swarm optimization (PSO) threshold for multi-stack fuel cell systems is proposed.
      Methods  For the hybrid power source system composed of multiple fuel cell stacks and batteries, a fuzzy logic energy management strategy based on the PSO algorithm was designed. By flexibly adjusting the number of fuel cell stacks and their individual output power based on the propulsion system load power and the battery state of charge (SOC), the control threshold of the system was optimized using PSO.
      Results  Matlab/Simulink simulation results show that this energy management strategy can quickly meet complex and changing load power requirements, and improve the system efficiency of the hybrid power source. Compared with traditional energy management strategies, the hydrogen consumption of the fuzzy logic-based and PSO threshold-based energy management strategies decreased by 18.96% and 31.48%, respectively.
      Conclusions  This intelligent energy management strategy is applicable to multi-stack fuel cell systems in hybrid propulsion ships, and can effectively improve the system efficiency of hybrid power sources and reduce hydrogen consumption.

     

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