The multi-objective optimization of dual-stator permanent magnet motors is crucial for improving their performance in various applications. This study introduces a composite algorithm aimed at optimizing these motors by balancing multiple objectives effectively. By integrating advanced computational techniques, the approach addresses critical aspects such as efficiency, torque characteristics, and thermal performance. The dual-stator configuration inherently offers enhanced magnetic flux, but optimizing its parameters can significantly augment overall motor efficiency and reliability. This research leverages intricate algorithms to navigate the complex multi-dimensional design space, ensuring that the motor’s performance metrics align with specific operational requirements. The findings demonstrate that adopting a composite algorithmic strategy can lead to substantial gains in motor performance, making it an invaluable approach for industries relying on advanced motor technologies.
