Diseño De Algoritmo De Control Mediante Aprendizaje Por Refuerzo Usando Matlab, Para Estaciones De Carga Rápida (36 Kw, 400 V) De Vehículos Eléctricos
This thesis presents the design of a control algorithm based on deep reinforcement learning, aimed at regulating the output voltage of a Boost-Boost power converter. This converter will be powered by a simulated solar panel array, applied to fast charging for electric vehicles. For the project devel...
- Autores:
-
Peralta Guzman, Diego
- Tipo de recurso:
- Tesis
- Fecha de publicación:
- 2024
- Institución:
- Universidad Antonio Nariño
- Repositorio:
- Repositorio UAN
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.uan.edu.co:123456789/12184
- Acceso en línea:
- https://repositorio.uan.edu.co/handle/123456789/12184
- Palabra clave:
- Aprendizaje por refuerzo profundo
Carga rápida
Convertidor doblador Boost
Paneles solares
Deep reinforcement learning
fast charging
Boost-Boost converter
solar panels
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivs 2.5 Colombia
| Summary: | This thesis presents the design of a control algorithm based on deep reinforcement learning, aimed at regulating the output voltage of a Boost-Boost power converter. This converter will be powered by a simulated solar panel array, applied to fast charging for electric vehicles. For the project development, the Matlab platform was used, where a complete simulation environment was designed, enabling the integration of all necessary components and blocks for the system’s implementation. |
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