Speaker
Description
Compared to the commonly used H and T-A methods for superconducting simulations, the J model offers a computational speed improvement of one to two orders of magnitude. However, due to inherent limitations, the J model is currently unable to simulate superconducting electrical devices containing ferromagnetic materials, such as superconducting motors. In this work, the existing J model is enhanced by coupling it with a magnetic network model, resulting in a J-Φ coupled model. This model is applied for the first time to the simulation of superconducting motors, which has the potential of achieving a 2-3 times speed improvement compared to the conventional T-A method. The fast computational model developed in this study provides an efficient platform for optimizing and controlling superconducting motors in future applications. This study will systematically describe the process of J-Φ coupled model and the accuracy in the calculation such as AC loss and magnetic field distribution, as well as possible future application scenarios.