Identification of Hysteresis Parameters of Current Transformer J-A Model Based on Improved Whale Algorithm

In the accurate modeling of current transformer core, the representation of ferromagnetic material characteristics is a key point. The J-A hysteresis model has the advantages of less parameters and clear physical meaning, and is widely used in research. Aiming at the problems of low precision and time consuming in the optimization algorithm of J-A model parameter identification, this paper proposes an improved whale search algorithm to realize the fast and accurate identification of J-A hysteresis model parameters. The method combines the improved search strategy and adaptive weight, which can make the algorithm have good global search ability and local search ability, and converge to the global optimal value quickly. The new search strategy is applied to the simulation of flux and current, and the simulation results are compared with the simulation results of other algorithms. The results show that the convergence speed is faster and the identification accuracy is higher when the algorithm is used to identify the model parameters. The simulated hysteresis loop based on the parameters identified by the algorithm is in good agreement with the measured curve, which verifies the practicability, effectiveness and superiority of the algorithm.