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

• Main Authors: Long Chen, Qiongyang Yi, Tong Ben, Zeyu Zhang, Youhua Wang
• Format: Article
• Language: English
• Published: AIP Publishing LLC 2021-01-01
• Series: AIP Advances
• Online Access: http://dx.doi.org/10.1063/9.0000030

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.