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Chen, Z., Bai, B., Chen, D., Chai, W..  2018.  Direct-Current and Alternate-Decay-Current Hybrid Integrative Power Supplies Design Applied to DC Bias Treatment. IEEE Transactions on Power Electronics. 33:10251–10264.
This paper proposes a novel kind of direct-current and alternate-decay-current hybrid integrative magnetization and demagnetization power supplies applied to transformer dc bias treatment based on a nanocomposite magnetic material. First, according to the single-phase transformer structure, one dc bias magnetic compensation mechanism was provided. The dc bias flux in the transformer main core could be eliminated directionally by utilizing the material remanence. Second, for the rapid response characteristic of the magnetic material to an external magnetic field, one positive and negative dc magnetization superimposed decaying ac demagnetization hybrid integrative power supplies based on single-phase rectifier circuit and inverter circuit was designed. In order to accurately control the magnetic field strength by which a good de/-magnetization effect could be achieved, this paper adopts the double-loop control technology of the magnetic field strength and magnetizing current for the nanocomposite magnetic state adjustment. Finally, two 10 kVA transformers and the experiment module of the hybrid integrative power supplies were manufactured and built. Experimental results showed that the integrated power supplies have good de/-magnetization effect and practicability, proving the validity and feasibility of the proposed scheme.
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.
Chandrasekaran, S. K., Crawford, A. C..  2017.  Demagnetization of a Complete Superconducting Radiofrequency Cryomodule: Theory and Practice. IEEE Transactions on Applied Superconductivity. 27:1–6.

A significant advance in magnetic field management in a fully assembled superconducting radiofrequency cryomodule has been achieved and is reported here. Demagnetization of the entire cryomodule after assembly is a crucial step toward the goal of average magnetic flux density less than 0.5 μT at the location of the superconducting radio frequency cavities. An explanation of the physics of demagnetization and experimental results are presented.

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.

Neubauer, A., Fritsch, K. M., Elsässer, A..  2016.  Optimized electromagnetic and manufacturing design for a BLDC-motor substituting rare earth magnets. 2016 6th International Electric Drives Production Conference (EDPC). :207–210.

Substituting neodymium with ferrite based magnets comes with the penalty of significant reduced magnetic field energy. Several possibilities to compensate for the negative effects of a lower remanence and coercivity provided by ferrite magnets are presented and finally combined into the development of a new kind of BLDC-machine design. The new design is compared to a conventional machine on the application example of an electric 800 W/48 V automotive coolant pump.