AI-Enhanced Design and Multi-Objective Optimization of a High-Efficiency Induction Motor using FEA Techniques and Liquid Cooling

Abstract

This paper presents a comprehensive design methodology and performance analysis of a high-efficiency electric motor optimized for industrial applications. The proposed motor integrates advanced electromagnetic design techniques, high-performance material selection (including soft magnetic composites and high-grade copper windings), and innovative thermal management strategies to achieve superior torque density, reduced energy losses, and enhanced operational reliability. Finite Element Analysis (FEA) and computational modelling were employed to optimize the motor’s electromagnetic and thermal characteristics. Experimental results demonstrate a 12% increase in efficiency compared to conventional industrial motors, along with a 15% improvement in torque density under continuous operation. Furthermore, the motor’s cooling system ensures stable performance even under high-load conditions, making it suitable for demanding industrial environments. The study includes a comparative analysis with IEC-standard motors, highlighting the proposed design’s advantages in terms of energy savings, durability, and cost-effectiveness.