Abstract
Gas foil bearings-rotor system is particularly crucial to affect the performance and energy efficiency of the air compressor for hydrogen fuel cell vehicles. However, the existing air compressors have the problem of poor stability and high energy consumption. To address this issue, the systematic multi-optimization method of the bearings-rotor system considering both the larger load and lower power consumption based on artificial neural network intelligent regression model and nondominated sorting genetic algorithms III is presented in this work for the first time. The optimal bearings-rotor system with a load capacity of 192.03 N and a power consumption of 15.38W is obtained. Under the optimum system, the input factors combination composed of the nominal clearance of 7.9 μm, foil thickness of 0.17 mm, half bump length of 0.942 mm, friction coefficient of 0.047, and rotation speed of 28462 rpm is determined. Compared to the average value of the original sample, the optimal system increases by 3.49 times in load capacity while decreasing by 30 % in power consumption. These findings and methodology are highly favorable for hydrogen energy vehicles with respect to improving stability and energy efficiency.
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