A Novel Energy Harvesting Technology

As the world shifts toward sustainable energy, harvesting wasted energy from everyday infrastructure has become a key research focus. One promising area is rail transport, where the movement of trains generates significant airflows—especially in tunnels. These airflows, often turbulent and impulsive, represent an untapped energy source.

This system combines drag-based and lift-based bladed elements with advanced control strategies to maximize energy capture from variable airflows.

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The Challenge: Wind Energy in Railway Tunnels

Railway tunnels present a unique fluid dynamic environment. When a train passes through a tunnel, it acts like a piston, pushing air ahead and drawing it in from behind. This creates:

• Piston effects

• Slipstreams

• Compression and expansion waves

These phenomena result in highly unsteady, turbulent, and multidirectional airflow—conditions that traditional wind turbines struggle to handle. Conventional horizontal-axis (HAWT) and vertical-axis (VAWT) wind turbines are often inefficient or unsafe in such settings due to:

• Rapid changes in wind direction and speed

• Risk of mechanical failure from debris or vibrations

• Space constraints and safety regulations

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The Solution: A Hybrid Drag-Lift Energy Harvester

The proposed system integrates two types of bladed devices (BDs), each optimized for different aerodynamic principles:

1. Drag-Based Bladed Device

• Uses flat blades that open to maximize drag during the active phase and close to minimize resistance during the return phase.

• Operates like a sailing vessel with tailwind.

• Converts translational motion into rotation via rack-and-pinion and freewheel mechanisms.
  
  

Governing Equations:

The extracted power $P_D$ is given by:

$$P_D=C_D\cdot \frac{1}{2}\rho \cdot N_{BE}\cdot S_{BE}\cdot v_f^3\cdot a_D\cdot (1-a_D{)}^2$$

Where:

• $C_D$: Drag coefficient

• $\rho$: Air density

• $N_{BE}$: Number of bladed elements in active phase

• $S_{BE}$: Reference surface area

• $v_f$: Undisturbed wind velocity

• $a_D$: Speed ratio $\frac{v_{BE}}{v_f}$

The maximum power is achieved at $a_D=\frac{1}{3}$, yielding:

$$C_p=\frac{4}{27}{C}_D\sigma$$

2. Lift-Based Bladed Device

• Uses airfoil-shaped blades that generate lift in both upward and downward strokes.

• Adjusts angle of attack dynamically to optimize performance.

• Operates in a double-acting configuration.

Governing Equations:

The power coefficient $C_p$ for the lift-based system is:

$$C_p=\sigma \cdot \sqrt{(1-a{)}^2+a_L^2}\cdot a_L[C_{L\theta }(1-a)-C_{D\theta }{a}_L]$$

Where:

• $a$: Axial interference factor

• $a_L$: Speed ratio $\frac{v_y}{v_f}$

• $C_{L\theta },C_{D\theta }$: Lift and drag coefficients at angle of attack $\theta$

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System Architecture and Control

The overall system is modular and scalable, consisting of:

• Multiple Wind Energy Systems (WES)

• Central Control Unit (CCU)

• Gearbox and Generator Group

• Sensors and Actuators

Control System Hierarchy

The control architecture is organized into four layers:

1. Hardware Layer: Sensors and actuators

2. Control Layer: Real-time parameter regulation

3. Mapping Layer: Stores optimal operating points

4. Local Management: Implements device-specific strategies

A Global Management Layer (GML) coordinates all subsystems, balancing power contributions and optimizing performance under transient conditions.

Performance and Real-World Potential

In a simulated railway tunnel scenario with a train speed of 15 m/s, the integrated system achieved:

• Maximum power: 2.56 kW at 788 rpm

• Peak torque: 5.46 kgm

• Efficiency: Comparable to or better than conventional micro-turbines

Advantages:

• Adaptability: Can be tailored to tunnel geometry and airflow patterns

• Robustness: Simplified mechanical structure reduces maintenance

• Safety: No high-speed rotating parts exposed

• Multi-functionality: Can redirect airflow to reduce passenger discomfort or aid braking

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Conclusion

This innovative hybrid energy harvesting system represents a significant step forward in sustainable infrastructure. By combining drag and lift principles with intelligent control systems, it effectively captures energy from highly variable airflows in railway tunnels—a context where conventional turbines fall short.

The technology is modular, scalable, and cost-effective, making it suitable for widespread deployment in rail networks worldwide. Future work will focus on site-specific implementations and real-world validation.