Numerical Modeling and Structure Optimization for Magnetic Levitation Planar Machine Using PCB Coils

Magnetically levitated (ML) systems that incorporate PCB coils represent a growing trend in precision machining, valued for their controllable current flow and high fill factor. The size of modern power devices is decreasing to enhance power density, minimize parasitic inductance, and reduce power losses. However, due to the high resistance of PCB coils, managing heat generation has become a significant area of study. This paper seeks to optimize PCB coil design to minimize power loss and control peak temperatures in ML systems, using a numerical model. An improved magnetic node model is employed to construct the magnetic fields of an ML system. The proposed optimization method considers the interdependencies among parameters to reduce overall power loss from coil resistance and switching losses in the H-bridge circuit, while enhancing heat dissipation efficiency in steady-state operation. A heuristic multi-objective optimization algorithm is employed to optimize the design of the ML actuator. The optimization process initially focuses on the PCB coils, with the magnet size held constant. Once the optimal coil parameters are identified, the magnet volume is optimized. By integrating a theoretical analysis with simulation, this approach effectively addresses the optimization challenges and achieves the desired performance for the ML actuator. Coils and magnets are constructed based on the optimized design and tested by the magnetic field simulation software Radia, confirming the feasibility of the approach. The method was also applied to a different type of ML system for comparison, demonstrating the universality of the proposed strategy. In this optimization effort, the maximum temperature reduction reached an impressive 50 degrees C