{"title":"基于NSGA-U算法的同步降压变换器多目标优化","authors":"Wei-Hsin Chang, Jiuhe Wang, Qili Chen","doi":"10.1109/ICMA.2016.7558766","DOIUrl":null,"url":null,"abstract":"This paper proposes a multi-objective optimization design method with the discrete variables for synchronous buck converter. This method defines three objective factors: minimize cost, minimize area and maximize efficiency, and a multi-objective optimization problem can be drawn with the objective function of assessment models of cost, area and loss and the constraint of the component database built by the parameter of MOSFETs, inductors and capacitors. This paper uses the NSGA-II algorithm to process the problem of a multi-objective optimization with discrete variables. The NSGA-II algorithm can find the Pareto optimal solution of a very large solution space which has hundreds of thousands feasible combinations of components, and the designers can make the reasonable choice of components by performing the trade-off analysis for the optimal solution when selecting the components. The simulation results demonstrate the feasibility of multi-objective optimization design method in this paper.","PeriodicalId":260197,"journal":{"name":"2016 IEEE International Conference on Mechatronics and Automation","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-objective optimization of synchronous buck converter based on NSGA-U algorithm\",\"authors\":\"Wei-Hsin Chang, Jiuhe Wang, Qili Chen\",\"doi\":\"10.1109/ICMA.2016.7558766\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a multi-objective optimization design method with the discrete variables for synchronous buck converter. This method defines three objective factors: minimize cost, minimize area and maximize efficiency, and a multi-objective optimization problem can be drawn with the objective function of assessment models of cost, area and loss and the constraint of the component database built by the parameter of MOSFETs, inductors and capacitors. This paper uses the NSGA-II algorithm to process the problem of a multi-objective optimization with discrete variables. The NSGA-II algorithm can find the Pareto optimal solution of a very large solution space which has hundreds of thousands feasible combinations of components, and the designers can make the reasonable choice of components by performing the trade-off analysis for the optimal solution when selecting the components. The simulation results demonstrate the feasibility of multi-objective optimization design method in this paper.\",\"PeriodicalId\":260197,\"journal\":{\"name\":\"2016 IEEE International Conference on Mechatronics and Automation\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Mechatronics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMA.2016.7558766\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Mechatronics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2016.7558766","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-objective optimization of synchronous buck converter based on NSGA-U algorithm
This paper proposes a multi-objective optimization design method with the discrete variables for synchronous buck converter. This method defines three objective factors: minimize cost, minimize area and maximize efficiency, and a multi-objective optimization problem can be drawn with the objective function of assessment models of cost, area and loss and the constraint of the component database built by the parameter of MOSFETs, inductors and capacitors. This paper uses the NSGA-II algorithm to process the problem of a multi-objective optimization with discrete variables. The NSGA-II algorithm can find the Pareto optimal solution of a very large solution space which has hundreds of thousands feasible combinations of components, and the designers can make the reasonable choice of components by performing the trade-off analysis for the optimal solution when selecting the components. The simulation results demonstrate the feasibility of multi-objective optimization design method in this paper.