Parameter identification of J-A hysteresis model based on simulated annealing and improved PSO algorithm

In this paper, an improved PSO algorithm based on simulated annealing is proposed, which combines simulated annealing algorithm and PSO algorithm. By using the global search ability of simulated annealing algorithm and the fast convergence performance of PSO algorithm, the parameters of hysteresis model can be identified quickly and accurately. The simulation of parameter identification of JA hysteresis model verifies that the proposed hybrid algorithm has higher fitting degree to hysteresis curve and higher precision of identified parameters, and it is not easy to fall into local optimal solution. At the same time, a dynamic J-A hysteresis model is established by introducing the loss of the core in the alternating magnetic field to evaluate the influence of dynamic loss on the magnetic internal energy, and the rapidity and effectiveness of the proposed algorithm for parameter identification in engineering applications considering eddy current loss and abnormal loss factors are verified.

Key words: transformer; Jile-Atherton model; Parameter identification; Simulated annealing algorithm; PSO algorithm