{"title":"基于ai的三相无刷直流电机无传感器转速估计","authors":"J. Srisertpol, A. Srikaew, P. Jawayon","doi":"10.1109/IWACI.2010.5585142","DOIUrl":null,"url":null,"abstract":"This paper describes a signal-based speed estimation of 3-Phase Brushless Direct Current (BLDC) motor using the relationship between commutation signal and Back Electromotive Force (Back-EMF). Both signals can directly be measured from each phase of motor's terminal. The relationship function between both signals is approximated and filtered to find Haft of phase voltage-Crossing Point and using Artificial Intelligence find coefficient of function and filter's parameters of each speed.","PeriodicalId":189187,"journal":{"name":"Third International Workshop on Advanced Computational Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"AI-based sensorless speed estimation of 3-phase BLDC motor\",\"authors\":\"J. Srisertpol, A. Srikaew, P. Jawayon\",\"doi\":\"10.1109/IWACI.2010.5585142\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a signal-based speed estimation of 3-Phase Brushless Direct Current (BLDC) motor using the relationship between commutation signal and Back Electromotive Force (Back-EMF). Both signals can directly be measured from each phase of motor's terminal. The relationship function between both signals is approximated and filtered to find Haft of phase voltage-Crossing Point and using Artificial Intelligence find coefficient of function and filter's parameters of each speed.\",\"PeriodicalId\":189187,\"journal\":{\"name\":\"Third International Workshop on Advanced Computational Intelligence\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Third International Workshop on Advanced Computational Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWACI.2010.5585142\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third International Workshop on Advanced Computational Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWACI.2010.5585142","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AI-based sensorless speed estimation of 3-phase BLDC motor
This paper describes a signal-based speed estimation of 3-Phase Brushless Direct Current (BLDC) motor using the relationship between commutation signal and Back Electromotive Force (Back-EMF). Both signals can directly be measured from each phase of motor's terminal. The relationship function between both signals is approximated and filtered to find Haft of phase voltage-Crossing Point and using Artificial Intelligence find coefficient of function and filter's parameters of each speed.
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