{"title":"一种高频变换器电路参数在线估计框架","authors":"Nicholas Green, Mohammed Agamy","doi":"10.1049/ell2.70230","DOIUrl":null,"url":null,"abstract":"<p>In this paper a parameter estimation method of high frequency switching power converters is proposed. Parameters are estimated through measurement of basic circuit voltage and current quantities and using simple feed forward neural networks to establish correlations between circuit parameter variations and general converter performance. This allows the estimation of internal semiconductor device or passive component parameters that would be challenging to measure directly. This approach serves as a promising enabler for power converter digital twins and for converter health monitoring. The proposed framework is developed and verified for an LLC resonant converter. Parameter predictions achieved mean absolute errors below 4.12% and an average MAE of 1.57% for all parameters.</p>","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70230","citationCount":"0","resultStr":"{\"title\":\"A Framework for Online Estimation of High Frequency Converter Circuit Parameters\",\"authors\":\"Nicholas Green, Mohammed Agamy\",\"doi\":\"10.1049/ell2.70230\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In this paper a parameter estimation method of high frequency switching power converters is proposed. Parameters are estimated through measurement of basic circuit voltage and current quantities and using simple feed forward neural networks to establish correlations between circuit parameter variations and general converter performance. This allows the estimation of internal semiconductor device or passive component parameters that would be challenging to measure directly. This approach serves as a promising enabler for power converter digital twins and for converter health monitoring. The proposed framework is developed and verified for an LLC resonant converter. Parameter predictions achieved mean absolute errors below 4.12% and an average MAE of 1.57% for all parameters.</p>\",\"PeriodicalId\":11556,\"journal\":{\"name\":\"Electronics Letters\",\"volume\":\"61 1\",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2025-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70230\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronics Letters\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/ell2.70230\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronics Letters","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/ell2.70230","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
A Framework for Online Estimation of High Frequency Converter Circuit Parameters
In this paper a parameter estimation method of high frequency switching power converters is proposed. Parameters are estimated through measurement of basic circuit voltage and current quantities and using simple feed forward neural networks to establish correlations between circuit parameter variations and general converter performance. This allows the estimation of internal semiconductor device or passive component parameters that would be challenging to measure directly. This approach serves as a promising enabler for power converter digital twins and for converter health monitoring. The proposed framework is developed and verified for an LLC resonant converter. Parameter predictions achieved mean absolute errors below 4.12% and an average MAE of 1.57% for all parameters.
期刊介绍：
Electronics Letters is an internationally renowned peer-reviewed rapid-communication journal that publishes short original research papers every two weeks. Its broad and interdisciplinary scope covers the latest developments in all electronic engineering related fields including communication, biomedical, optical and device technologies. Electronics Letters also provides further insight into some of the latest developments through special features and interviews.
Scope
As a journal at the forefront of its field, Electronics Letters publishes papers covering all themes of electronic and electrical engineering. The major themes of the journal are listed below.
Antennas and Propagation
Biomedical and Bioinspired Technologies, Signal Processing and Applications
Control Engineering
Electromagnetism: Theory, Materials and Devices
Electronic Circuits and Systems
Image, Video and Vision Processing and Applications
Information, Computing and Communications
Instrumentation and Measurement
Microwave Technology
Optical Communications
Photonics and Opto-Electronics
Power Electronics, Energy and Sustainability
Radar, Sonar and Navigation
Semiconductor Technology
Signal Processing
MIMO
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