Systematic Optimization of Electromagnet Hardware for Electromagnetic Suspension: A Fusion of Simulation and Multi-objective Optimization Techniques

This article introduces a novel multiobjective design optimization (MOO) framework for enhancing magnetically levitating (Maglev) systems. By integrating finite-element method (FEM) simulations and focusing on the dynamic interplay between mechanical and electromagnetic properties, as well as control system dynamics, our approach addresses the complex challenges of Maglev design, such as variable inductance, force production due to air-gap fluctuations, and magnetic saturation. The proposed framework facilitates the development of more efficient, reliable, and adaptable Maglev technologies. Through a simulated implementation, we demonstrate the framework's effectiveness in optimizing electromagnet design for improved system integration and performance, marking a significant advancement in electromechanical system optimization.