{"title":"PEM燃料电池系统多目标模糊粒子群优化","authors":"Ren Yuan, Zhong Zhidan, Zhang Bo, Lv Feng, Xu Huili","doi":"10.1109/ICAL.2010.5585365","DOIUrl":null,"url":null,"abstract":"This paper proposed multi-objective fuzzy particle swarm optimization (MOFPSO) for the Proton Exchange Membrane Fuel Cells (PEMFC) generation system. The PEM fuel cell generation system efficiency decreases as its output power increases. Thus, an optimum efficiency should exist and should result in a cost-effective PEM fuel cell generation system. In the optimization approach, the efficient and economic aspects are considered simultaneously. MOFPSO algorithm is used to find a set of Pareto optimal solutions with respect to the aforementioned objective functions. The performance of the proposed optimizer is demonstrated under various operating conditions. Both experimental and simulation results show the optimizer works well.","PeriodicalId":393739,"journal":{"name":"2010 IEEE International Conference on Automation and Logistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Multi-objective fuzzy particle swarm optimization in PEM fuel cell systems\",\"authors\":\"Ren Yuan, Zhong Zhidan, Zhang Bo, Lv Feng, Xu Huili\",\"doi\":\"10.1109/ICAL.2010.5585365\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposed multi-objective fuzzy particle swarm optimization (MOFPSO) for the Proton Exchange Membrane Fuel Cells (PEMFC) generation system. The PEM fuel cell generation system efficiency decreases as its output power increases. Thus, an optimum efficiency should exist and should result in a cost-effective PEM fuel cell generation system. In the optimization approach, the efficient and economic aspects are considered simultaneously. MOFPSO algorithm is used to find a set of Pareto optimal solutions with respect to the aforementioned objective functions. The performance of the proposed optimizer is demonstrated under various operating conditions. Both experimental and simulation results show the optimizer works well.\",\"PeriodicalId\":393739,\"journal\":{\"name\":\"2010 IEEE International Conference on Automation and Logistics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Automation and Logistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAL.2010.5585365\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Automation and Logistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAL.2010.5585365","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-objective fuzzy particle swarm optimization in PEM fuel cell systems
This paper proposed multi-objective fuzzy particle swarm optimization (MOFPSO) for the Proton Exchange Membrane Fuel Cells (PEMFC) generation system. The PEM fuel cell generation system efficiency decreases as its output power increases. Thus, an optimum efficiency should exist and should result in a cost-effective PEM fuel cell generation system. In the optimization approach, the efficient and economic aspects are considered simultaneously. MOFPSO algorithm is used to find a set of Pareto optimal solutions with respect to the aforementioned objective functions. The performance of the proposed optimizer is demonstrated under various operating conditions. Both experimental and simulation results show the optimizer works well.