Wireless Power Train for Electric Vehicles an optimization framework for efficient solar powered

Descripción del proyecto

Soluciones de recarga inteligentes para el futuro de la movilidad eléctrica

Uno de los principales obstáculos para la adopción generalizada de los vehículos eléctricos es la falta de comodidad de los sistemas de recarga actuales. Esta limitación, sumada a la persistente dependencia de la energía procedente de combustibles fósiles, frena los avances hacia un transporte climáticamente neutro. En el proyecto WPT for EV, respaldado por las acciones Marie Skłodowska-Curie, se desarrollará un sistema de recarga inalámbrica integrado con energía solar fotovoltaica y compatible con la red inteligente. Para garantizar una recarga automatizada e ininterrumpida, el sistema combina la transferencia inalámbrica de energía de alta eficiencia con un método híbrido de optimización que integra algoritmos evolutivos y aprendizaje por refuerzo. En conjunto, se mejorará el rendimiento de la recarga cuando varíe la disponibilidad de energía renovable. La solución contribuirá a aumentar la adopción de los vehículos eléctricos, reducir las emisiones y avanzar en los objetivos de la Unión Europea en materia de clima y transporte.

Objetivo

Climate neutrality by 2050, as envisioned under the European Green Deal, causes urgent transformations in the transportation sector, which handles nearly 25% of greenhouse gas emissions. The dominance of internal combustion engines must give way to sustainable, fully electric transportation systems. However, adopting electric vehicles (EVs) faces persisting barriers, particularly range anxiety, dependency on conventional energy, reliance on user intervention, and limitations of intermittent renewable power sources.

This project WPT for EV proposes a solar-photovoltaic (PV) integrated wireless EV charger with seamless utility grid support. This system eliminates fossil fuel reliance, ensures uninterrupted charging despite PV intermittency, and mitigates range anxiety through automated wireless operation that requires no user involvement.

The key objectives are to:
Enhance charging efficiency beyond 95%, surpassing existing wireless systems (85–90%).
Eliminate user dependency with automatic wireless charging.
Integrate renewable PV power with grid interconnection for continuous operation.

Support the EU Green Deal, Fit for 55, and AFIF infrastructure goals. The methodology employs a Hybrid Evolutionary-Reinforcement Optimization (HERO) technique. Genetic Algorithms (GA) are used for static design optimisation, such as sizing coils and predicting inverter operating frequencies under varying solar input. Reinforcement Learning (RL) dynamically fine-tunes system parameters, adjusting inductive coil values in real time to maintain resonance and maximise power transfer efficiency. This hybrid optimisation approach ensures robust static performance and adaptive dynamic control to efficiently deliver the required charging power. The proposed WPT for EV chargers offers a highly efficient, user-independent, renewable-powered solution for advancing EV adoption by combining PV integration.