Systemic Multi-Objective Optimization of Induction Motor-Driven Electromechanical Systems
Noureddine Ferchichi1, Houssem Ben Aribia2
1Ferchichi Noureddine, Department of Electrical and Electronics Engineering, Jazan University, Jazan, Saudi Arabia.
2Ben Aribia Houssem, Department of Electrical and Electronics Engineering, Jazan University, Jazan, Saudi Arabia.
Manuscript received on 20 December 2024 | First Revised Manuscript received on 02 January 2025 | Second Revised Manuscript received on 09 January 2025 | Manuscript Accepted on 15 January 2025 | Manuscript published on 30 January 2025 | PP: 25-30 | Volume-14 Issue-2, January 2025 | Retrieval Number: 100.1/ijitee.B104414020125 | DOI: 10.35940/ijitee.B1044.14020125
Open Access | Editorial and Publishing Policies | Cite | Zenodo | OJS | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The optimization of electromechanical systems, such as those involving induction motors and gearboxes, is crucial for improving energy efficiency, system performance, and reliability in industrial applications. This paper presents an advanced methodology for optimizing the energy efficiency of electromechanical systems, integrating both mechanical and electrical subsystems to minimize the system’s overall weight, energy losses, and transient response time. The optimisation problem is approached holistically, considering the interdependence of various system parameters and employing multi-objective optimisation techniques to address conflicting objectives. The analysis focuses on optimizing the gearbox speed ratio to minimize the relative weight of the motor-gearbox system while maintaining operational efficiency. A systematic approach, utilising convex surrogate modelling and multi-stage gearboxes, is proposed to enhance the scalability of the solution. The results demonstrate the existence of optimal gearbox speed ratios for various motor sizes and configurations, providing insights into the best design choices for minimising system weight and optimising performance. These findings apply to a range of real-world systems, including electric vehicles and industrial machinery, where minimising weight and optimising energy efficiency are crucial for enhancing overall system performance and reducing operational costs.
Keywords: Energy Efficiency, Multi-Objective Optimization, Minimum System Weight, Systemic Approach.
Scope of the Article: Electrical and Electronics