Hoyeon Hwang, Dongju Park, Wonchang Lee, K. Hong, Kiseok Kim
{"title":"Mathematical models with temperature compensation for InSb and GaAs hall sensors using linear regression method","authors":"Hoyeon Hwang, Dongju Park, Wonchang Lee, K. Hong, Kiseok Kim","doi":"10.23919/ELINFOCOM.2018.8330692","DOIUrl":null,"url":null,"abstract":"In this paper, we designed the mathematical models for InSb and GaAs devices which are hall sensors with different characteristics and confirmed the efficacy of the two models through simulation in MATLAB. Assuming the limitations on the computational capability of the microprocessor which will be used to compensate the nonlinearity due to temperature for the two sensors in the real system, the linear regression for temperature compensation is divided into several sections and performed in first order polynomial. The error rate between the curve fitted by the linear regression and the data received from the hall sensor was calculated. The performance evaluation was carried out and it was confirmed that the error rate was within 1%.","PeriodicalId":413646,"journal":{"name":"2018 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Electronics, Information, and Communication (ICEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ELINFOCOM.2018.8330692","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this paper, we designed the mathematical models for InSb and GaAs devices which are hall sensors with different characteristics and confirmed the efficacy of the two models through simulation in MATLAB. Assuming the limitations on the computational capability of the microprocessor which will be used to compensate the nonlinearity due to temperature for the two sensors in the real system, the linear regression for temperature compensation is divided into several sections and performed in first order polynomial. The error rate between the curve fitted by the linear regression and the data received from the hall sensor was calculated. The performance evaluation was carried out and it was confirmed that the error rate was within 1%.
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