GA-based Optimization of a Surface-mounted Permanent Magnet Synchronous Motor

Renewable Energies Environment and Power Quality Journal 2026 Open access

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Authors: Pedro Cruz-Romero, Álvaro Rodríguez del Nozal, J.M. Mauricio, Miguel Angel González Cagigal
DOI: 10.24084/reepqj25-548
Cited by: 0

Abstract

The paper deals with a simple procedure to design surface mounted permanent magnet synchronous machines, based on genetic algorithms scripted in Python library deap. The paper includes the formulas involved in the motor design, the operational constraints, the fitness functions (torque constant and motor weight), as well as the results obtained after running the algorithm in a case study. Key words. fitness function, genetic algorithms, surface mounted permanent magnet, motor constant, Pareto front.

Fields of Study & Subjects

Electric Motor Design and Analysis Sensorless Control of Electric Motors Metaheuristic Optimization Algorithms Research

Publication details

Journal / source
Renewable Energies Environment and Power Quality Journal
Volume
25
Issue
3
Pages
279–284
Publication date
1 February 2026