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PerSeO: Un paquete de Python para optimizar antenas y dispositivos de RF en entornos de alta frecuencia
(Universidad ECCI, 2024) Ángel Melgarejo, Jaime Andrés; Páez Diaz, Daniela; Mora, Sergio; Vera Vera, Jhon; Restrepo, Oscar
This paper presents the development and evaluation of PerSeO, a Python-based software package that integrates the Particle Swarm Optimization (PSO) algorithm with Ansys HFSS for optimizing radiofrequency (RF) devices. By focusing on the optimiza- tion of a patch antenna, we demonstrate how PerSeO efficiently adjusts design dimensions to achieve a specific resonance frequency while maintaining adequate impedance matching. The application of PSO within PerSeO has shown significant improvements in electromagnetic parameters, confirming its effectiveness and rapid convergence to optimal solutions. The modular architecture of PerSeO allows for easy customization and extension, making it applicable to a wide range of RF optimization problems. Detailed documentation and a comprehensive user manual support users in effectively implementing and utilizing PerSeO’s capabilities. Our results highlight PerSeO as a powerful and versatile tool for RF device optimization, reducing the time and resources required to achieve optimal designs. Future enhancements could include new fitness functions, parallel processing techniques, and integration with additional HFSS reports to further expand its applicability in RF engineering.