Análisis de gestión energética mediante ciclos personalizados en vehículos eléctricos/híbridos para entornos urbanos orográficos [Energy management analysis using customised cycles in electric/hybrid vehicles for urban environments with steep terrain]
DOI:
https://doi.org/10.62574/rmpi.v5iTecnologia.414Palabras clave:
gestión energética, ciclos de conducción, vehículos eléctricos, (Fuente: Tesauro UNESCO).Resumen
La gestión energética eficiente en vehículos eléctricos e híbridos representa un desafío tecnológico complejo que requiere estrategias adaptadas a condiciones locales específicas. Esta revisión sistemática analiza 20 estudios científicos publicados entre 2018 y 2024, siguiendo el protocolo PRISMA, para examinar estrategias de gestión energética fundamentadas en ciclos de conducción personalizados. Los resultados evidencian que la personalización de ciclos mejora la precisión de estimaciones de consumo en 18%, mientras que técnicas de inteligencia artificial como redes neuronales temporales convolucionales alcanzan errores menores al 1.5% en estimación de estado de carga. Las estrategias de gestión energética basadas en aprendizaje por refuerzo Q-learning reducen la degradación de baterías hasta 20% comparado con métodos tradicionales. La integración de variables topográficas y climáticas resulta fundamental para optimizar el rendimiento en regiones andinas, donde pendientes superiores al 4% incrementan el consumo energético en 13.7%.
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Derechos de autor 2025 Antonio Gabriel Castillo-Medina, Esteban Fernando López-Espinel, Juan Diego Zurita-Vargas , Mario Fernando Vargas-Brito
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