Irreversible demagnetization analysis of RWAFPM motor using modified MEC algorithm

This paper aims to present a modified MEC algorithm for demagnetization modeling of the PM motor. One of the major issues that the designers of the permanent magnet (PM) motors are faced with is the demagnetization of magnets because of high temperatures and armature reaction. Demagnetization will weaken the magnetic properties of the magnet and lead to a reduction in the performance of the motor. Therefore, it is essential to provide appropriate methods for modeling this phenomenon. One of these methods that has a compromise between accuracy and time consumption is the magnetic equivalent circuit (MEC). In this paper, the MEC method is used for modeling the demagnetization phenomenon for the newly introduced ring winding axial flux PM (RWAFPM) motor. The proposed algorithm can take the demagnetization into account through a time-stepping model and also correct the value of the knee point flux density.

The modified MEC method is used for demagnetization modeling. The modified algorithm can take into account demagnetization and also renew the knee point at each step to increase the accuracy of the modeling. In addition, the proposed algorithm has a very high and fast execution speed so that the computation time of the MEC algorithm compared to the FEM model is reduced from 3 h to 35 s. In this case, the simulations have been performed on a core i5@ 2.3 GHz/8GB computer. The FEM model is used to verify the validity of the MEC results.

The obtained results show that at the high temperature, RWAFPM motor is severely vulnerable to demagnetization. At the temperature of 140°C, the demagnetization rate of 35% has occurred. So, it is necessary to use the high-temperature magnet in this motor or modify the motor structure in terms of demagnetization tolerant capability.

The RWAFPM motor is introduced for use in ship propulsion and traction systems. For this reason, an accurate estimation of demagnetization tolerant of this motor in different working conditions can show the strengths and weaknesses of this structure.