Tetsuya Aoki

Improvement of Convergence Characteristics of 1-D Dynamic Magnetic Field Analysis With Hysteresis for Iron Loss Estimation

In previous studies on precise computation methods of iron loss, it has been shown that the 1-D dynamic magnetic field analysis with hysteresis in post-processing is effective. However, there is a problem in that the hysteresis makes the convergence of nonlinear iterations unstable. This paper proposes a stabilization method for the 1-D dynamic magnetic field analysis with hysteresis. The proposed method is characterized as an approach for improving the initial value and the step size in the Newton-Raphson method. The results of this paper showed that the convergence characteristic of the nonlinear 1-D magnetic field analysis for variety flux density waveforms of each part in an electric motor is improved using the proposed method.