AI-Driven Flight Trajectory Optimization Using Flywheel Energy Storage for Enhanced Fuel Efficiency

Monday, October 20, 2025: 11:00 AM
Ms. mahi mishra , VIT BHOPAL UNIVERSITY, bhopal, madhya pradesh, India
Ms. aanal suthar , VIT BHOPAL UNIVERSITY, bhopal, madhya pradesh, India
Ms. fiza ansari , VIT BHOPAL UNIVERSITY, bhopal, madhya pradesh, India
Combining expertise will allow the companies to conduct research in several aspects of fuel consumption, carbon emissions (linked directly to the establishment of sustainability targets and dealing with rising operational costs), and how this might work towards creating a clean sky. Conventional aircraft systems burn the entire fuel without exploiting energy recovery in non-cruise operational phases, such as taxiing and landing roll. Recent developments in flywheel energy storage systems and Artificial Intelligence (AI) can rectify these shortcomings by harnessing kinetic energy and saving total fuel utilisation. The integration of these technologies is crucial for yielding game-changing solutions that optimise energy use in all aircraft operations.

The focus of this research is the development of a system that:

  1. Conserves fuel during active phases of flight by integrating flywheel energy storage with legacy aviator propulsion systems.
  2. Utilizes artificial intelligence algorithms to dynamically calculate and optimize flight paths as well as energy management in real time for best fuel economization while abiding by safety and operation criteria.Translate withClassifierOutput
  3. Showcases a scalable and practical solution for real-world aviation that supports the industry's sustainable development.

Using methods such as Flywheel Integration, AI Control System, Simulation and Testing.

      Resulting in:

      • System-wide Fuel Efficiency
      • Environmental Impact
      • Engineering Feasibility
      • Taxi-out and Landing Roll

      The study shows the potential of combining flywheel energy storage systems with AI-controlled flight path optimization to achieve trajectory-dependent fuel savings in aircraft. The system also minimizes emissions and operational costs by recovering and reusing energy that is usually lost in the process. Leveraging cutting-edge developments in AI, energy storage, and aviation engineering in a novel mix, provides a path for scalable sustainable aviation. This concept, with its potential results, offers a revolutionary path for the aviation industry to meet its long-term sustainability targets.

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