Research on Optimization of Magnet Current of Maglev Vehicle Based on Levitation Control Algorithm

Based on the medium-low speed maglev vehicle with mid-set air spring, the dynamic model with three levitation frames are established in UM (Universal Mechanism). The performance of the vehicle at different speeds is analyzed. The results show that the dynamic performance can meet the requirements of the maglev vehicle running at higher speeds. However, the magnet current also increases with the increase of running speed, which leads to an increase in the weight of the magnet and the controller, and then the drive unit of maglev vehicle becomes heavier. Then three types of levitation control algorithms are established in MATLAB/Simulink: PID feedback control, PI+P hybrid control, PID+fuzzy control. For the optimization of magnet current, the control performance of the maglev vehicle to the track excitation under different levitation control algorithms is analyzed. The following conclusions can be drawn: on the basis of keeping the suspension stability, different levitation control algorithms have different magnet current responses with same running speed and vehicle parameters. PID+fuzzy control can effectively lower the magnet current fluctuation and reduce the r.m.s. value of magnet current; PI+P hybrid control can effectively decline the impact of mutation interference on the current and reduce the current fluctuation range.