中国电机工程学报2024，Vol.44Issue(6)：2340-2349,后插22,11.DOI:10.13334/j.0258-8013.pcsee.230258
一种基于分数阶微积分的CCM Boost变换器准在线无源参数的数字孪生辨识方法
A Quasi-online Digital Twin Identification Method for Passive Parameters of CCM Boost Converters Based on Fractional Calculus
摘要
Abstract
Due to the advantages of high-cost performance,accuracy and digitization,digital twin has become an advanced technology for fault trending and predictive maintenance of power electronic converters.However,the current digital twin models of power electronic converters fail to consider the fractional characteristics of actual inductors and capacitors,posing a challenge for accurate prediction and fault diagnosis.To address this problem,this paper proposes a prediction-correction digital twin model for power electronic circuits based on fractional calculus.The inductance(L)and capacitance(C)are identified at different fractional orders using a digital twin parameter identification method based on particle swarm optimization(PSO),and the equivalent series resistance(ESR)is calculated.Compared to existing methods,the proposed method not only improves the identification accuracy of the actual inductance and capacitance,but also identifies the fractional parameters at different fractional orders and capacitances.Finally,implementation of continuous conduction mode(CCM)Boost converter with different inductances,capacitances and fractional orders is presented.Besides,different working conditions and identification numbers are considered.The experimental results verify the effectiveness of the proposed model and method.关键词
数字孪生/分数阶/Boost变换器/参数辨识/粒子群优化Key words
digital twin/fractional-order/Boost converter/parameters identification/particle swarm optimization(PSO)分类
信息技术与安全科学引用本文复制引用
马铭遥,韩添侠,陈强,王鼎奕,徐君..一种基于分数阶微积分的CCM Boost变换器准在线无源参数的数字孪生辨识方法[J].中国电机工程学报,2024,44(6):2340-2349,后插22,11.基金项目
国家自然科学基金项目(51977054).Project Supported by National Natural Science Foundation of China(51977054). （51977054）
