- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | XU Fengqiu, QIU Yi, HE Jiawen, XU Xianze. Remanence Compensation of Maglev Planar Motor Based on Digital Twin Model[J]. Journal of Southwest Jiaotong University, 2025, 60(4): 1050-1059. doi: 10.3969/j.issn.0258-2724.20240556
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A remanence compensation method for permanent magnet arrays was proposed to enhance the control performance of maglev planar motors after demagnetization faults, and the effectiveness of the proposed method was verified by a digital twin model. Firstly, a digital twin framework for maglev planar motors based on a five-dimensional digital twin model was constructed, and the components of the five-layer architecture were clarified. Secondly, the relationship between the magnetic field around the mover and the residual magnetization intensity was explored by using a magnetic charge node model to obtain a remanence inversion expression. Then, the inverted remanence data were introduced into the motion decoupling process to derive the control current after remanence compensation. Digital twin data of maglev planar motors with different demagnetization distributions were used to obtain remanence values through inversion. Multiple trajectory tracking simulation experiments were conducted to compare motion simulations under three conditions: no demagnetization, neglecting demagnetization effects, and remanence inversion compensation. The results show that compared with neglecting demagnetization effects, the remanence inversion compensation method reduces the root mean square error of horizontal ramp trajectory tracking by 56.5% and the maximum error by 40.9%. The setting time in planar motion step response is decreased by 41.3%, and the overshoot is reduced by 15.7%. When a circle contour is tracked, the root mean square of contour error is decreased by 85.0%, and the maximum error is reduced by 38.9%.
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