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Fuel economy using the global optimization of the Fuel Cell Hybrid Power Systems

机译：使用燃料电池混合动力系统的全局优化实现燃油经济性

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The aim of this paper is to compare an optimal and a sub-optimal strategy for the Fuel Cell Hybrid Power Systems based on Maximum Power Point tracking algorithms (with global feature or not) with the basic energy management strategy, namely the static Feed-Forward strategy considered as reference. The fuel economy is used as the unique performance indicator. The gaps in fuel economy for two Real-Time Optimization strategies based on Global Extremum Seeking algorithm and Perturb & Observe algorithm are compared to highlight the advantages of the global optimization strategies. Up to 5 L fuel economy was obtained for optimal strategies compared to sub-optimal ones. Also, the gaps in fuel economy are estimated for the proposed strategies using two levels of the FC current slope. The results of this study obtained for constant load are validated on a variable and unknown profile of the load power as well.
机译：本文的目的是将基于最大功率点跟踪算法（具有或不具有全局功能）的燃料电池混合动力系统的最优和次优策略与基本能量管理策略（即静态前馈）进行比较。策略作为参考。燃油经济性用作独特的性能指标。比较了两种基于全局极值搜索算法和Perturb＆Observe算法的实时优化策略在燃油经济性方面的差距，以突出全局优化策略的优势。与次优策略相比，最优策略可实现高达5 L的燃油经济性。同样，使用FC电流斜率的两个水平来为拟议的策略估算燃油经济性的差距。对于恒定负载获得的这项研究结果也可以在负载功率的可变和未知曲线上得到验证。

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