基于模拟退火改进PSO算法的J-A磁滞模型参数辨识  

Parameter Identification of J-A Hysteresis Model Based on Hybrid Algorithms of SA and Improved PSO

作　　者：林峻宁 严柏平 冯浩文 陈聪 黄大卓 沈春城 LIN Junning;YAN Baiping;FENG Haowen;CHEN Cong;HUANG Dazhuo;SHEN Chuncheng(School of Automation,Guangdong University of Technology,Guangzhou 510006,China)

机构地区：[1]广东工业大学自动化学院,广东广州510006

出　　处：《变压器》2024年第2期26-34,共9页Transformer

基　　金：广东省自然科学基金(2018A030313010);广州市科技计划项目(202102021135)。

摘　　要：本文作者提出了一种基于模拟退火改进PSO算法,将模拟退火算法和PSO算法融合,利用模拟退火算法的全局搜索能力与PSO算法的快速收敛性能,可实现磁滞模型参数的快速、精确辨识。J-A磁滞模型参数辨识的仿真验证了所提混合算法对于磁滞曲线的拟合程度、辨识所得参数精度均更高,且不易于陷入局部最优解。同时,通过引入铁心在交变磁场中产生的损耗部分,建立了动态J-A磁滞模型以评估动态损耗对磁内能的影响,验证了所提出算法在考虑涡流损耗和异常损耗因素下工程应用中参数辨识的快速性与有效性。An improved PsO algorithm based on simulated annealing in this paper is proposed to address the problems of low identification accuracy and long operation time in the J-A model parameter identification.This algorithm can achieve rapid and accurate jdentification of magnetic hysteresis model parameters by combining the global search capability of simulated annealing and the fast convergence performance of the PsO algorithm.The simulation verification of the J-A hysteresis model parameter identification demonstrates that the proposed hybrid algorithm has a higher fiting degree and identification accuracy for the hysteresis curve and is less likely to fall into a locally optimal solution.Moreover,by introducing the loss part generated by the core in the alternating magnetic field,a dynamic J-A magnetic hysteresis model is established to evaluate the impact of dynamic losses on magnetic internal energy.This verifies the effectiveness and efficiency of the proposed algorithm in parameter identification considering eddy current losses and abnormal losses factors in engineering applications.

关 键 词：变压器 Jile-Atherton模型 参数辨识 模拟退火算法 PSO算法 

分 类 号：TM406[电气工程—电器]