Parameter identification of Preisach model based on velocity-controlled particle swarm optimization method

Long Chen,Youhua Wang,Zeyu Zhang,Qiongyang Yi,Tong Ben

doi:10.1063/9.0000030

Abstract

The Preisach model is widely used to simulate the magnetic performance of transformers and motors in industrial applications. However, its parameter identification problem is still a complicated task. This paper proposed a new parameter identification method based on the velocity-controlled particle swarm optimization (VCPSO) algorithm combined with the closed-form Everett function. Firstly, the Preisach model is built through the closed-form Everett function, which gives an explicit form Preisach model. Secondly, the Preisach model’s parameter identification is realized by using the VCPSO algorithm, which only needs the limiting static hysteresis loop of the material. During the optimization process, the particle velocity is automatically adjusted to avoid falling into the optimal local solution. Finally, the obtained results are compared with the experimental hysteresis loop of the B30P150 silicon steel.

Highlights

With the rapid development of Ultra-High Voltage (UHV) power transmission systems, higher requirements are put forward for electrical equipment efficiency
The Preisach model is widely used to simulate the magnetic performance of transformers and motors in industrial applications
This paper proposed a new parameter identification method based on the velocitycontrolled particle swarm optimization (VCPSO) algorithm combined with the closed-form Everett function

Summary

INTRODUCTION

With the rapid development of Ultra-High Voltage (UHV) power transmission systems, higher requirements are put forward for electrical equipment efficiency. The classical Preisach model (CPM) is widely used to simulate magnetic performance due to its high accuracy and implementation efficiency.. The classical Preisach model’s solving process needs to integrate the Preisach distribution function and build a vast Everett matrix, which is highly computational memory usage. In 2016, Szabo Zsolt proposed a numerical Preisach model based on the closed-form Everett function.. A powerful parameter identification method with fast convergence speed and high calculation accuracy needs to be further studied and discussed.. A stochastic parameter identification method of the parametric Preisach model with closed-form Everett function is proposed and discussed. The proposed method is proved fast convergence with high accuracy and successful identification rate, which is of great significance for the researchers in the area of electromagnetic analysis of electrical equipment

THE IMPLEMENTATION OF PREISACH MODEL

Measurement of quasi-static hysteresis loops

Parameters identification by velocity-controlled particle swarm optimization

RESULTS AND DISCUSSIONS

CONCLUSION