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Kim, Chang-Woo, Jang, Gang-Heyon, Shin, Kyung-Hun, Jeong, Sang-Sub, You, Dae-Joon, Choi, Jang-Young.  2020.  Electromagnetic Design and Dynamic Characteristics of Permanent Magnet Linear Oscillating Machines Considering Instantaneous Inductance According to Mover Position. IEEE Transactions on Applied Superconductivity. 30:1—5.

Interior permanent magnet (IPM)-type linear oscillating actuators (LOAs) have a higher output power density than typical LOAs. Their mover consists of a permanent magnet (PM) and an iron core, however, this configuration generates significant side forces. The device can malfunction due to eccentricity in the electromagnetic behavior. Thus, here an electromagnetic design was developed to minimize this side force. In addition, dynamic analysis was performed considering the mechanical systems of LOAs. To perform a more accurate analysis, instantaneous inductance was considered according to the mover's position.

Song, Juncai, Zhao, Jiwen, Dong, Fei, Zhao, Jing, Xu, Liang, Wang, Lijun, Xie, Fang.  2019.  Demagnetization Modeling Research for Permanent Magnet in PMSLM Using Extreme Learning Machine. 2019 IEEE International Electric Machines Drives Conference (IEMDC). :1757–1761.
This paper investigates the temperature demagnetization modeling method for permanent magnets (PM) in permanent magnet synchronous linear motor (PMSLM). First, the PM characteristics are presented, and finite element analysis (FEA) is conducted to show the magnetic distribution under different temperatures. Second, demagnetization degrees and remanence of the five PMs' experiment sample are actually measured in stove at temperatures varying from room temperature to 300 °C, and to obtain the real data for next-step modeling. Third, machine learning algorithm called extreme learning machine (ELM) is introduced to map the nonlinear relationships between temperature and demagnetization characteristics of PM and build the demagnetization models. Finally, comparison experiments between linear modeling method, polynomial modeling method, and ELM can certify the effectiveness and advancement of this proposed method.
Gonzalez, A. G., Millinger, J., Soulard, J..  2016.  Magnet losses in inverter-fed two-pole PM machines. 2016 XXII International Conference on Electrical Machines (ICEM). :1854–1860.

This article deals with the estimation of magnet losses in a permanent-magnet motor inserted in a nut-runner. This type of machine has interesting features such as being two-pole, slot-less and running at a high speed (30000 rpm). Two analytical models were chosen from the literature. A numerical estimation of the losses with 2D Finite Element Method was carried out. A detailed investigation of the effect of simulation settings (e.g., mesh size, time-step, remanence flux density in the magnet, superposition of the losses, etc.) was performed. Finally, calculation of losses with 3D-FEM were also run in order to compare the calculated losses with both analytical and 2D-FEM results. The estimation of the losses focuses on a range of frequencies between 10 and 100 kHz.

Zhang, Q., Ma, Z., Li, G., Qian, Z., Guo, X..  2016.  Temperature-dependent demagnetization nonlinear Wiener model with neural network for PM synchronous machines in electric vehicle. 2016 19th International Conference on Electrical Machines and Systems (ICEMS). :1–4.

The inevitable temperature raise leads to the demagnetization of permanent magnet synchronous motor (PMSM), that is undesirable in the application of electrical vehicle. This paper presents a nonlinear demagnetization model taking into account temperature with the Wiener structure and neural network characteristics. The remanence and intrinsic coercivity are chosen as intermediate variables, thus the relationship between motor temperature and maximal permanent magnet flux is described by the proposed neural Wiener model. Simulation and experimental results demonstrate the precision of temperature dependent demagnetization model. This work makes the basis of temperature compensation for the output torque from PMSM.

Zhuoping Yu, Junxian Wu, Lu Xiong.  2014.  Research of stability control of distributed drive electric vehicles under motor failure modes. Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014 IEEE Conference and Expo. :1-5.

With the application and promotion of electric vehicles, vehicle security problems caused by actuator reliability have become increasingly prominent. Firstly, the paper analyses and sums motor failure modes and their effects of permanent magnet synchronous motor (PMSM) , which is commonly used on electric vehicles. And then design a hierarchical structure of the vehicle control strategies and the corresponding algorithms, and adjust based on the different failure modes. Finally conduct simulation conditions in CarSim environment. Verify the control strategy and algorithm can maintain vehicle stability and reduce the burden on driver under motor failure conditions.