Intelligent Control for Type I Partial Power Converters in EV Charging Systems: Twin-Delayed Deep Deterministic Policy Gradient Approach

Daniel Pesantez*, Oswaldo Menendez, H. Renaudineau, S. Kouro, S. Rivera, Jose Rodriguez

*Autor correspondiente de este trabajo

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

In recent years, the electric vehicle (EV) industry has experienced significant advancements, simultaneously driving substantial progress in battery technology. The evolution of battery systems necessitates enhancements in charging infrastructure to attain elevated power levels during the charging process, thereby minimizing charging time. Various algorithms have been developed for driving battery charging; however, these algorithms necessitate the creation of diverse controllers to generate precise trigger signals for the semiconductors within the various power converters utilized in charging stations. This work presents the design of an innovative model-free control system for Type I impedance network Partial Power Converter (PPC) in which a Deep Reinforcement Learning (DRL) agent generates control signals during the different charging stages. Particularly, a Twin-Delayed Deep Deterministic Policy Gradient (TD3) algorithm is used to substitute the inner control loop of traditional control systems. To this end, different agents were designed, trained, and tested inside a built simulation environment. It is worth noting that TD3-based control allows for the optimal functionality of a type I impedance network PPC within the context of EV battery charging applications, according to the specified CC-CV charging algorithm. Empirical results revealed that the battery system reached an 80% state of charge in under 8 minutes starting from an initial 20%.

Idioma originalInglés
Título de la publicación alojada2024 IEEE International Conference on Automation/26th Congress of the Chilean Association of Automatic Control, ICA-ACCA 2024
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9798350378115
DOI
EstadoPublicada - 2024
Publicado de forma externa
Evento2024 IEEE International Conference on Automation/26th Congress of the Chilean Association of Automatic Control, ICA-ACCA 2024 - Santiago, Chile
Duración: 20 oct. 202423 oct. 2024

Serie de la publicación

Nombre2024 IEEE International Conference on Automation/26th Congress of the Chilean Association of Automatic Control, ICA-ACCA 2024

Conferencia

Conferencia2024 IEEE International Conference on Automation/26th Congress of the Chilean Association of Automatic Control, ICA-ACCA 2024
País/TerritorioChile
CiudadSantiago
Período20/10/2423/10/24

Nota bibliográfica

Publisher Copyright:
© 2024 IEEE.

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