Achievement Of J-A Hysteresis Model Based On A Hybrid Algorithm

As one of the classical macro-models, Jiles-Atherton hysteresis model of the ferromagnetic material is a phenomenological model based on physics. In the thesis, a modified J-A static hysteresis model is presented, and the magnetic flux density is the independent variable in the model. Considering the dynamic loss, a modified J-A dynamic hysteresis model with the magnetic flux density as the independent variable is deduced in the thesis. Then, the procedure of calculating the model equation by Runge-kutta method is given. Further more, chaos optimization method, genetic method and simulated annealing method are studied. By analyzing, the drawback of the three methods above, are given. Then, a new optimization method is proposed by mixing the advance of three methods. The new method is more efficient than the three traditional methods when solving the problem of nonlinear model's parameter identification. Last, the parameters of the modified J-A model are calculated by the new method presented in the thesis, and the calculated results are well agreed to the measured results.