Experimental analysis and physics-informed optimization algorithm for ejector in fuel cells based on boundary-breaking and dimension reduction

Chao Li, Jianqin Fu, Yuting Huang and Xilei Sun

Renewable Energy, 2024, vol. 237, issue PC

Abstract: As an important auxiliary component in renewable devices such as fuel cells and solar cooling systems, ejectors have demonstrated excellent potential due to their parasitic power-free, low emissions, low noise, and cost-effectiveness. However, the existing design and optimization algorithms for ejectors still lack effective methods for selecting optimized parameters and delineating boundaries. In order to fully consider the definition method of parameter boundaries in optimization, a physical-informed algorithm is proposed to realize the functions of boundary-breaking and dimension reduction. The results show that the indicators Mp, Ms, Mo, and fobj are 2.06, 3.78, 2.62, and 2.80 times higher than the non-dominated sorting genetic algorithm - II, and the dimension reduction is 58.8 %. Additionally, a continuous mapping for multi-objective programming is established to reflect the physical implications inside the ejector. An empirical formula (R2 = 0.9917) is derived between the entrainment ratio, the radius of the mixing section, and the radius of the nozzle. This method not only achieves the function of boundary breaking and dimension reduction, but also can be used to guide the design and optimization of ejectors with uncertain boundary parameters.

Keywords: Ejector; Fuel cell; Physics-informed algorithm; Boundary-breaking; Dimension reduction; Empirical formula (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:237:y:2024:i:pc:s096014812401824x

DOI: 10.1016/j.renene.2024.121756

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