Mathematical modeling and optimization of gas foil bearings-rotor system in hydrogen fuel cell vehicles

被引:5
|
作者
Shi, Ting [1 ,3 ]
Wang, Huaiyu [2 ]
Yang, Wenming [3 ]
Peng, Xueyuan [1 ]
机构
[1] Xi An Jiao Tong Univ, State Key Lab Multiphase Flow Power Engn, Xian 710049, Peoples R China
[2] Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China
[3] Natl Univ Singapore, Fac Engn, Dept Mech Engn, Singapore 117575, Singapore
关键词
Hydrogen fuel cell vehicles; Machine learning; Gas foil bearings -rotor system; Energy efficiency; ARTIFICIAL NEURAL-NETWORK; PERFORMANCE; PREDICTION; COMPRESSOR;
D O I
10.1016/j.energy.2023.130129
中图分类号
O414.1 [热力学];
学科分类号
摘要
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 mu m, 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.
引用
收藏
页数:14
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