{"title":"Hybrid Modeling for LCC Circuit Based on Machine Learning","authors":"Xi Lu, Shuhao Yang, Saijun Mao","doi":"10.1109/peas53589.2021.9628776","DOIUrl":null,"url":null,"abstract":"This paper investigates a hybrid modeling method for LCC resonate circuit. The hybrid model includes traditional mathematical model and machine learning error model. First, the traditional mathematical modeling method and equivalent circuit are presented. Second, a practical LCC circuit is simulated based on PLECS and real hardware parameter, and actually output data is obtained. Then, based on the comparison between real data and mathematical model output data, the error data is obtained. Third, machine learning algorithm is introduced to model this error data, and with a proper weight coefficient, a hybrid model for LCC circuit is obtained. Finally, comparison the hybrid model output under different working condition with simulation results can certify the effectiveness and advancement of this proposed method.","PeriodicalId":268264,"journal":{"name":"2021 IEEE 1st International Power Electronics and Application Symposium (PEAS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 1st International Power Electronics and Application Symposium (PEAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/peas53589.2021.9628776","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper investigates a hybrid modeling method for LCC resonate circuit. The hybrid model includes traditional mathematical model and machine learning error model. First, the traditional mathematical modeling method and equivalent circuit are presented. Second, a practical LCC circuit is simulated based on PLECS and real hardware parameter, and actually output data is obtained. Then, based on the comparison between real data and mathematical model output data, the error data is obtained. Third, machine learning algorithm is introduced to model this error data, and with a proper weight coefficient, a hybrid model for LCC circuit is obtained. Finally, comparison the hybrid model output under different working condition with simulation results can certify the effectiveness and advancement of this proposed method.