CONSISTENCY OPTIMIZATION OF 3 kW PROTON EXCHANGE MEMBRANE FUEL CELL STACK BASED ON ARTIFICIAL NEURAL NETWORK

Shi Lei; Xu Sichuan; Liu Ze

doi:10.19912/j.0254-0096.tynxb.2020-1426

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Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (8) : 498-503. DOI: 10.19912/j.0254-0096.tynxb.2020-1426

CONSISTENCY OPTIMIZATION OF 3 kW PROTON EXCHANGE MEMBRANE FUEL CELL STACK BASED ON ARTIFICIAL NEURAL NETWORK

Shi Lei, Xu Sichuan, Liu Ze

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Abstract

The consistency of each cell's voltage is the key to improving PEMFC stack performance. Based on the experimental data of 3 kW stack, this paper utilizes an artificial neural network（ANN） model to optimize the gas supply parameters, including airflow rate, hydrogen pressure and excess air coefficient. Simultaneously, the power and consistency characteristics of the stack before and after optimization are compared and analyzed. The results show that the C_V and power parameters can achieve best when the inlet pressure of hydrogen is 0.128 MPa, the inlet flow rate of air is 11 g/s, and the excess air coefficient is 6.4.

Key words

proton exchange membrane fuel cell / durability / consistency / artificial neural network / bucket effect

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Shi Lei, Xu Sichuan, Liu Ze. CONSISTENCY OPTIMIZATION OF 3 kW PROTON EXCHANGE MEMBRANE FUEL CELL STACK BASED ON ARTIFICIAL NEURAL NETWORK[J]. Acta Energiae Solaris Sinica. 2022, 43(8): 498-503 https://doi.org/10.19912/j.0254-0096.tynxb.2020-1426

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