考虑可逆分量的解析Preisach磁滞模型及其特征参数辨识算法  

Analytical Preisach Hysteresis Model Considering Reversible Component and Its Characteristic Parameter Identification Algorithm

作　　者：陈彬 王斐然[2] 万妮娜 唐波 黄力 CHEN Bin;WANG Feiran;WAN Nina;TANG Bo;HUANG Li(Hubei Provincial Engineering Technology Research Center for Power Transmission Line,Yichang 443002,China;College of Electrical Engineering&New Energy,China Three Gorges University,Yichang 443002,China;Yichang Electric Company,State Grid Hubei Electric Power Company,Yichang 443002,China)

机构地区：[1]湖北省输电线路工程技术研究中心,宜昌443002 [2]三峡大学电气与新能源学院,宜昌443002 [3]国网湖北省电力有限公司宜昌供电公司,宜昌443002

出　　处：《高电压技术》2023年第11期4766-4774,共9页High Voltage Engineering

基　　金：国家自然科学基金青年科学基金(52107006);湖北省自然科学基金面上项目(2021CFB149)。

摘　　要：基于洛伦兹函数的解析Preisach模型具有形式简便、分布函数易于确定等优势,但如果考虑可逆磁化分量,模型的复杂程度和参数会显著增加,导致用于传统模型参数辨识的解析或神经网络等方法不再适用。为此,首先通过引入可逆磁化分量,构建一种考虑可逆分量的解析Preisach模型;然后,分析了各个特征参数对磁滞回线形状的影响规律,并且结合循环迭代法与粒子群算法,提出一种针对考虑可逆分量解析Preisach模型的特征参数混合寻优算法;最后,将所提磁滞模型及其参数辨识算法得到的磁滞回线计算值与实测值进行对比。结果表明,该模型及其参数辨识算法的最大平均相对误差为4.49%,验证了该方法的准确性和有效性。The analytical Preisach model based on the Lorentz function has the advantages of simple form and easy determination of distribution function,which can be applied to the simulation of hysteresis and loss characteristics of core.However,at present,analytical or neural network methods are usually used to identify its parameters.The above methods have some shortcomings in dealing with multi-dimensional complex problems,such as low accuracy and slow convergence speed.In addition,if the reversible magnetization component needs to be considered,the model complexity and model parameters will increase significantly,which aggravates the difficulty of parameter identification.Therefore,this paper first constructs an analytical Preisach model considering the reversible component by introducing the reversible magnetization component.Then,the influence of various characteristic parameters on the shape of hysteresis loop is analyzed,and a hybrid optimization algorithm for characteristic parameters considering the reversible component analysis Preisach model is proposed by combining the cyclic iterative method and particle swarm optimization algorithm.Finally,the calculated hysteresis loops obtained by the proposed hysteresis model and its parameter identification algorithm are compared with the measured values.The results show that the maximum average relative error of the model and its parameter identification algorithm is 4.49%,which verifies the accuracy and effectiveness of the proposed method.

关 键 词：磁滞特性 PREISACH模型 可逆磁化分量 粒子群算法 参数辨识 

分 类 号：TM271[一般工业技术—材料科学与工程]