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Working zone for a least-squares support vector machine for modeling polymer electrolyte fuel cell voltage

机译:用于建模聚合物电解质燃料电池电压的最小二乘的工作区

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摘要

The least squares support vector machine method has been successfully applied to modeling the transient behavior of polymer electrolyte fuel cells; this paper analyzes the credibility and definition of its reliable working zone when dealing with multiple load changes. The transient model based on the least squares support vector machine is initially established. Then, the effects of the fuel cell system's setup and exterior load behavior on the transient model are investigated. Artificial data from experimentally-validated Simulink simulations are used, by which extreme working conditions could be taken into account. We found that the fuel cell system's setup with intensive sampling brings about better model performance than that with a sparse sampling interval, as sharp peaks are well characterized when intensive sampling is applied and more information on the fuel cell system is provided to the transient model. Furthermore, the performance of the transient model is better when smoother load changes are imposed on the system, and so a large ramp time and small ramp value are preferable. A working zone for a least squares support vector machine to model polymer electrolyte fuel cell is defined, for which an absolute error is used. Based on the acceptable level of error in the fuel cell system, a set of feasible combinations of its setup and exterior load changes is regulated. Accuracy in the transient model is achieved when the fuel cell runs within the working domain.
机译:最小二乘支持向量机方法已成功应用于建模聚合物电解质燃料电池的瞬态行为;本文分析了在处理多重负荷变化时可靠工作区的可信度和定义。最初建立基于最小二乘支持向量机的瞬态模型。然后,研究了燃料电池系统的设置和外部负载行为对瞬态模型的影响。使用来自实验验证的Simulink模拟的人工数据,通过该模拟可以考虑极端工作条件。我们发现燃料电池系统的集约采样设置具有比具有稀疏采样间隔的更好的模型性能,因为当施加密集采样并且提供有关燃料电池系统的更多信息被提供给瞬态模型时,表征尖锐的峰值。此外,当在系统上施加更平稳的负载变化时,瞬态模型的性能更好,因此优选大的斜坡时间和小的斜坡值。限定了用于模型聚合物电解质燃料电池的最小二乘支持向量机的工作区,其中使用绝对误差。基于燃料电池系统中可接受的误差水平,调节其设置和外部负载变化的一系列可行组合。当燃料电池在工作结构域内运行时,实现了瞬态模型中的精度。

著录项

  • 来源
    《Applied Energy》 |2021年第1期|116191.1-116191.11|共11页
  • 作者单位

    Forschungszentrum Julich Inst Energy & Climate Res IEK 14 Elect Proc Engn D-52425 Julich Germany|Rhein Westfal TH Aachen Modeling Elect Proc Engn Aachen Germany;

    Forschungszentrum Julich Inst Energy & Climate Res IEK 14 Elect Proc Engn D-52425 Julich Germany;

    Forschungszentrum Julich Inst Energy & Climate Res IEK 14 Elect Proc Engn D-52425 Julich Germany|Rhein Westfal TH Aachen Modeling Elect Proc Engn Aachen Germany;

    Forschungszentrum Julich Inst Energy & Climate Res IEK 14 Elect Proc Engn D-52425 Julich Germany|Rhein Westfal TH Aachen Modeling Elect Proc Engn Aachen Germany;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Polymer electrolyte fuel cells; Data-driven method; Least squares support vector machine; Statistical noise; Model suitability;

    机译:聚合物电解质燃料电池;数据驱动方法;最小二乘支持向量机;统计噪声;模型适用性;

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