{"title":"基于遗传算法的SCR动态模型参数辨识与仿真","authors":"Ren Hongjuan, Lou Diming, Zhu Jian, Luo Yiping","doi":"10.2174/1874123101509010062","DOIUrl":null,"url":null,"abstract":"The Selective Catalytic Reduce (SCR) is studied. The unknown parameters of the SCR kinetic model equations are fitted based on the Genetic Algorithm (GA), which is in the range of the allowable error, compared to the experimental data. Then in AVL Boost software, the simulation results of SCR reaction are obtained. Compared to the test data, the simulation results prove that the parameter identification is effective. At last, the SCR reaction is simulated in AVL Boost, and at the same exhaust temperature, the effect of GHSV and NSR on the SCR reaction is studied.","PeriodicalId":22933,"journal":{"name":"The Open Chemical Engineering Journal","volume":"36 1","pages":"62-66"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic Model Parameter Identification and Simulation of SCR Based on Genetic Algorithm\",\"authors\":\"Ren Hongjuan, Lou Diming, Zhu Jian, Luo Yiping\",\"doi\":\"10.2174/1874123101509010062\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Selective Catalytic Reduce (SCR) is studied. The unknown parameters of the SCR kinetic model equations are fitted based on the Genetic Algorithm (GA), which is in the range of the allowable error, compared to the experimental data. Then in AVL Boost software, the simulation results of SCR reaction are obtained. Compared to the test data, the simulation results prove that the parameter identification is effective. At last, the SCR reaction is simulated in AVL Boost, and at the same exhaust temperature, the effect of GHSV and NSR on the SCR reaction is studied.\",\"PeriodicalId\":22933,\"journal\":{\"name\":\"The Open Chemical Engineering Journal\",\"volume\":\"36 1\",\"pages\":\"62-66\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Open Chemical Engineering Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/1874123101509010062\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Open Chemical Engineering Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1874123101509010062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic Model Parameter Identification and Simulation of SCR Based on Genetic Algorithm
The Selective Catalytic Reduce (SCR) is studied. The unknown parameters of the SCR kinetic model equations are fitted based on the Genetic Algorithm (GA), which is in the range of the allowable error, compared to the experimental data. Then in AVL Boost software, the simulation results of SCR reaction are obtained. Compared to the test data, the simulation results prove that the parameter identification is effective. At last, the SCR reaction is simulated in AVL Boost, and at the same exhaust temperature, the effect of GHSV and NSR on the SCR reaction is studied.