Analysis of Self‐Optimisation Control Strategy for Speed Tracking and Making Dynamic Characteristics of Permanent Magnet Contactor

To improve the making dynamic characteristics of permanent magnet (PM) contactors and monitor the motion speed of the moving iron core, a speed tracking self‐optimisation control strategy is proposed. The displacement of the moving iron core during the making process is dynamically segmented, and the mechanical motion equation is used to monitor the moving iron core's speed accurately. Mixed control data of the moving iron core's operation speed are collected as sample data. Neural networks are employed to fit the speed prediction curve to identify speed inflection points, based on which the control strategy is optimised. Dynamic adjustments to the coil excitation achieve intelligent closed‐loop control of the making process. Using the finite element method, a dynamic mathematical model of the PM contactor's making process was established by coupling the voltage balance equation and D'Alembert's mechanical motion equation. MATLAB software was used to simulate the dynamic characteristics of the contactor under the speed tracking self‐optimisation control strategy, and the simulation results were consistent with experimental data. An experimental platform was built to test the proposed self‐optimisation control scheme. The results show that this method effectively reduces the final speed of the moving iron core, minimises the first and second rebounds caused by collisions between the movable and stationary contacts, reduces the length of the contact and pull arcs, and significantly enhances the mechanical and electrical lifespan of the contactor.