Improved EL Model of Long Stator Linear Synchronous Motor Via Analytical Magnetic Coenergy Reconstruction Method
Electromagnetic-suspension (EMS)-type maglev, based on long stator linear synchronous motor (LSLSM), suffers from the flux linkage and thrust ripple. This is due to the non-sinusoidal airgap magnetic field distribution caused by the slot effect and end effect. In this article, it is intended to addr...
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Veröffentlicht in: | IEEE transactions on magnetics 2020-08, Vol.56 (8), p.1-13 |
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Sprache: | eng |
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Zusammenfassung: | Electromagnetic-suspension (EMS)-type maglev, based on long stator linear synchronous motor (LSLSM), suffers from the flux linkage and thrust ripple. This is due to the non-sinusoidal airgap magnetic field distribution caused by the slot effect and end effect. In this article, it is intended to address this issue by establishing a nonlinear mathematical model of LSLSM for real-time simulation and controller design, considering the spatial harmonics and core saturation. The Euler-Lagrange (EL) model is improved by means of coenergy and then applied to obtain the general equations of LSLSM. At first, the variation in coenergy in LSLSM regarding the mover position and stator current are analyzed, in the presence of spatial harmonics and core saturation. Afterward, an analytical model of coenergy is constructed by two Fourier basis vectors of mover position and torque angle, and a coefficient matrix polynomial of stator current magnitude. Then, a new model of LSLSM is derived based on the coenergy model and EL method. The parameters of the model can be obtained from the numerical data of coenergy in all operation ranges via finite-element analysis (FEA). Finally, the new model of LSLSM and its propulsion system are integrated in MATLAB/Simulink setup. The simulation results show that the improved EL model can achieve satisfactory accuracy compared with the FEA results well, whereas the computational efficiency is improved largely. |
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ISSN: | 0018-9464 1941-0069 |
DOI: | 10.1109/TMAG.2020.3002964 |