Performance Analysis of Low Temperature Solid Oxide Fuel Cell Based on Artificial Intelligence Technology

Abstract

In order to solve the problems of poor output performance and large output oscillation of traditional low-temperature solid oxide fuel cells, artificial intelligence technology was introduced in this paper to analyze the performance of low-temperature solid oxide fuel cells. Firstly, the steady-state control system of the battery was constructed, and the three-dimensional structure design and electrical performance optimization of the battery were realized. Then, the electrode potential induction analysis model was constructed to analyze the carbon / metal oxide electrode materials with stable mechanical and electrochemical properties. Thirdly, combined with the three-phase regulation of the battery electrode, the microstructure area in the fuel cell electric field is controlled. Finally, according to the fuel cell output voltage, the fuel cell ion mass conservation model is constructed. Artificial intelligence is used to obtain the optimal solution of fuel cell voltage output, so as to complete the analysis of fuel cell steady-state performance. The simulation results show that this method can control the output of the low-temperature solid oxide fuel cell well and reduce the output oscillation of the cell, which has a certain theoretical reference significance for the performance of the cell.