Tang Chunsen, Deng Pengqi, W. Zhihui, Huang Yongcan, Dai Lin
{"title":"Parameter optimization method for the wireless charging system of mowing robot","authors":"Tang Chunsen, Deng Pengqi, W. Zhihui, Huang Yongcan, Dai Lin","doi":"10.1109/WOW.2017.7959375","DOIUrl":null,"url":null,"abstract":"This paper proposed a parameter optimization design method for the wireless charging system of mowing robot. The circuit topology for wireless charging is given according to the demand analysis of charging device. The boundary constraints of the system parameters are obtained by analyzing the characteristics of the wireless charging system and its performance requirements. Then the main parameters of the system are designed by seeking the optimal solution of the boundary constraints using a genetic algorithm. The feasibility of this design method is verified by simulation results.","PeriodicalId":242505,"journal":{"name":"2017 IEEE PELS Workshop on Emerging Technologies: Wireless Power Transfer (WoW)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE PELS Workshop on Emerging Technologies: Wireless Power Transfer (WoW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOW.2017.7959375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper proposed a parameter optimization design method for the wireless charging system of mowing robot. The circuit topology for wireless charging is given according to the demand analysis of charging device. The boundary constraints of the system parameters are obtained by analyzing the characteristics of the wireless charging system and its performance requirements. Then the main parameters of the system are designed by seeking the optimal solution of the boundary constraints using a genetic algorithm. The feasibility of this design method is verified by simulation results.