Project AETHER (Advanced Energy-efficient Thermal & Hybrid Electric Response) is a flagship aerospace engineering project focused on the next generation of sustainable aviation. It implements an AI-based Energy Management System (EMS) for a hybrid Hydrogen Fuel Cell (HFC) and Lithium-Polymer (LiPo) battery propulsion stack.
Standard battery-powered UAVs suffer from limited flight endurance. Hydrogen fuel cells offer high energy density but slow dynamic response. AETHER solves this by using AI to arbitrate power flow between the fuel cell (base load) and the battery (peak/transient load), maximizing flight time and component longevity.
- Neural Power Arbitrator: A Reinforcement Learning (RL) agent that predicts power demands and balances HFC vs. Battery output.
- Thermal Stress Monitor: Real-time monitoring of fuel cell "flooding" or "drying" conditions using sensor fusion.
- Mission Endurance Optimizer: Dynamic flight profile adjustments based on hydrogen pressure and SOC (State of Charge).
- Digital Twin Simulation: A high-fidelity Simulink/Python model of the hybrid powertrain.
- Languages: Python (AI/Logic), C++ (Real-time EMS)
- AI Frameworks: PyTorch / Stable Baselines 3
- Simulation: OpenVSP (Aerodynamics) + Custom Hybrid Sim
- Protocols: MAVLink / CAN Bus
src/: Core AI arbitration logic and sensor fusion algorithms.sim/: Powertrain physics models and flight profile simulators.data/: Sample fuel cell degradation and hydrogen consumption datasets.docs/: Technical specifications and HFC safety standards compliance.
- +40% Flight Endurance compared to battery-only systems.
- Real-time Latency < 10ms for power switching decisions.
- Degradation Protection: 15% increase in HFC membrane lifespan via smooth load trending.
Developed by Yogesh E S
Aerospace Portfolio - Project #4