Optimization of variable cross-section scroll based on self-adaptive NSGA- algorithm

doi:10.13245/j.hust.210312

IR > 机电工程学院

	Optimization of variable cross-section scroll based on self-adaptive NSGA- algorithm
	Liu T(刘涛)1 ; Zhao RQ(赵睿琦)1; Sun YJ(孙永吉)1,2
	2021-03-23
发表期刊	Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition)
ISSN	1671-4512
卷号	49 期号:3 页码:63-68
摘要	In the optimization design of scroll, considering merely the geometric performance as an optimization objective often results in the low mechanical performance of the scroll compressors. Therefore, a new multi-objective optimization method was proposed based on self-adaptive second-generation non-dominated sorting genetic algorithm (NSGA-), which balances mechanical and geometric performance of variable cross-section scroll. First, the mathematical model of the axial gas force and compression ratio of the scroll were established based on the analytical characteristic parameters of the scroll profile composed of the base circle involute and higher-ordered curve. Then, the multi-objective optimization design was carried out, which takes the minimum axial force and the maximum compression ratio as the target function. A crossover operator and a mutation operator that can self-adjust according to the evolution state of the population were introduced to improve the efficiency of NSGA- algorithm and the distribution uniformity of the optimal solution. Lastly, the Pareto optimal solution set of variable cross-section scroll was obtained. Three representative scrolls in the optimal solution set are compared with traditional variable cross-section scrolls, and the maximum axial gas force is reduced by 3.20%, 1.08% and 1.90%, the compression ratio is increased by 5.37%, 6.64% and 3.35%, respectively. Results show that the optimization proposed is effective in obtaining both mechanical and geometric optimal design. © 2021, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.
关键词	Genetic algorithms Geometry Multiobjective optimization Optimal systems Pareto principle Scroll compressors Distribution uniformity Mechanical performance Mutation operators Non- dominated sorting genetic algorithms Optimal solution sets Optimization design Pareto optimal solutions Variable cross section
DOI	10.13245/j.hust.210312
收录类别	EI
语种	中文
出版者	Huazhong University of Science and Technology
EI入藏号	20211710250553
EI主题词	Structural optimization
EI分类号	618.1 Compressors ; 921 Mathematics ; 921.5 Optimization Techniques ; 961 Systems Science
引用统计	无
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/148441
专题	机电工程学院
作者单位	1.兰州理工大学机电工程学院; 2.兰州工业学院机电工程学院
第一作者单位	机电工程学院
第一作者的第一单位	机电工程学院
推荐引用方式 GB/T 7714	Liu T,Zhao RQ,Sun YJ. Optimization of variable cross-section scroll based on self-adaptive NSGA- algorithm[J]. Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition),2021,49(3):63-68.
APA	刘涛,赵睿琦,&孙永吉.(2021).Optimization of variable cross-section scroll based on self-adaptive NSGA- algorithm.Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition),49(3),63-68.
MLA	刘涛,et al."Optimization of variable cross-section scroll based on self-adaptive NSGA- algorithm".Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) 49.3(2021):63-68.