Enhancing brushless DC motor wheel design using single and multi-objective heat transfer search optimization approach

This study introduces and explores a groundbreaking single objective Heat Transfer Search (HTS) algorithm and decomposition-oriented Multi-Objective Heat Transfer Search (MOHTS/D) algorithm, specifically devised to address intricate issues in designing brushless direct current wheel motors in real-world scenarios. Drawing upon the principles established in the recently conceptualized thermodynamics laws grounded Heat Transfer Search algorithm, it harmonizes the conduction, convection and radiation stages to maintain a stable equilibrium between local intensification and global diversification during the search process. The aim is to pinpoint Pareto optimal solutions while verifying their encompassing characteristics through the methodical application of uniform weight vector sorting and Euclidean distance tactics within the conceived posteriori technique. To sidestep challenges such as local optimum confinement, heightened computational intricacy and reliability deficiencies, a decomposition-oriented strategy is embraced. The efficacy of the HTS and MOHTS/D algorithms has been scrutinized by subjecting it to rigorous analysis across Brushless Direct Current Motors (BLDC). Findings emphasize the formidable potential of HTS and MOHTS/D as a resilient optimization tool when measured against other recognized optimizers in the sphere of tangible, significant brushless direct current wheel motor design challenges. Notably, HTS and MOHTS/D demonstrates superior prowess in identifying optimal solutions across various Pareto fronts, surpassing other notable algorithms in this domain.