Abstract:
The growing demand for self-sustaining electric vehicles highlights the limited adaptability of conventional
onboard renewable energy systems to dynamic environmental and vehicular conditions. This study
proposes a Vehicle-Mounted Wind–Solar Hybrid Renewable Energy System (VMW-WEH++) integrating
an Adaptive Resonant Energy Converter (AREC) with a Predictive Hybrid Energy Management (P-HEM)
framework for intelligent multi-source power coordination. The system operates in a state-aware manner:
solar energy is prioritized during vehicle motion to avoid aerodynamic losses, while wind energy is
maximized during stationary or idle states based on predicted availability. AREC replaces conventional
Maximum Power Point Tracking (MPPT) converters by dynamically tuning its resonant LC network to
maintain impedance matching for both Photovoltaic (PV) and micro-turbine inputs, achieving conversion
efficiencies exceeding 95% with reduced switching losses. The P-HEM framework combines medium-term
forecasting using Prophet and short-term prediction via a Temporal Convolutional Network (TCN),
enabling proactive energy scheduling. A hybrid battery–supercapacitor storage architecture ensures
voltage stability and reduced battery stress. MATLAB/Simulink results demonstrate improved efficiency,
higher usable harvested energy, and enhanced SoC stability and adaptive energy management
