Design and Optimization Workflow for Industrial Induction Machines

Abstract

The design and optimization of industrial induction machines require a systematic approach to meet performance, efficiency, and manufacturing constraints. This paper presents a structured workflow that integrates finite element methods, analytical modeling, and optimization techniques to enhance machine design. The methodology consists of defining manufacturer constraints, developing electromagnetic and thermal models, and optimizing machine parameters using the Non-Dominated Sorting Genetic Algorithm II. The proposed approach ensures high efficiency, minimal losses, and manufacturability while reducing computational time. A case study demonstrates the effectiveness of the workflow and highlights significant improvements in machine performance after optimization.