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Aerodynamics and Sensing Analysis for Efficient Drone-Based Parcel Delivery

Avishkar Seth, Alice James, Endrowednes Kuantama, Subhas Mukhopadhyay, Richard Han

Abstract

In an era of rapid urbanization and e-commerce growth, efficient parcel delivery methods are crucial. This paper presents a detailed study of the aerodynamics and sensing analysis of drones for parcel delivery. Utilizing Computational Fluid Dynamics (CFD), the study offers a comprehensive airflow analysis, revealing the aerodynamic forces affecting drone stability due to payload capacity. A multidisciplinary approach is employed, integrating mechanical design, control theory, and sensing systems to address the complex issue of parcel positioning. The experimental validation section rigorously tests different size payloads and their positions and impact on drones with maximum thrusts of 2000 gf. The findings prove the drone's capacity to lift a large payload that covers up to 50 percent of the propeller, thereby contributing to optimizing drone designs and sustainable parcel delivery systems. It has been observed that the drone can lift a large payload smoothly when placed above the drone, with an error rate as low as 0.1 percent for roll, pitch, and yaw. This work paved the way for more versatile, real-world applications of drone technology, setting a new standard in the field.

Aerodynamics and Sensing Analysis for Efficient Drone-Based Parcel Delivery

Abstract

In an era of rapid urbanization and e-commerce growth, efficient parcel delivery methods are crucial. This paper presents a detailed study of the aerodynamics and sensing analysis of drones for parcel delivery. Utilizing Computational Fluid Dynamics (CFD), the study offers a comprehensive airflow analysis, revealing the aerodynamic forces affecting drone stability due to payload capacity. A multidisciplinary approach is employed, integrating mechanical design, control theory, and sensing systems to address the complex issue of parcel positioning. The experimental validation section rigorously tests different size payloads and their positions and impact on drones with maximum thrusts of 2000 gf. The findings prove the drone's capacity to lift a large payload that covers up to 50 percent of the propeller, thereby contributing to optimizing drone designs and sustainable parcel delivery systems. It has been observed that the drone can lift a large payload smoothly when placed above the drone, with an error rate as low as 0.1 percent for roll, pitch, and yaw. This work paved the way for more versatile, real-world applications of drone technology, setting a new standard in the field.

Paper Structure

This paper contains 9 sections, 5 equations, 9 figures, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. System Methodology
  4. Airflow Analysis
  5. Payload Position Validation
  6. Experimental Evaluation
  7. Airlfow tests and Balancing Validation
  8. Flight tests
  9. Conclusion

Figures (9)

  • Figure 1: The schematic representation of the geometric relationship between the dimensions of the box placed above the drone and the eight airflow variations on and around the propeller slipstream
  • Figure 2: CFD simulation images of the UAV when no payload is placed depicting the Velocity [m/s] of the propellers (a) Bottom View (b) Side View
  • Figure 3: CFD simulation images of the UAV when a payload is placed depicting a higher aerodynamic disturbance sensed around the propellers (a) Bottom View (b) Side View
  • Figure 4: Photographs of the three different drones with varying dimensions and configurations
  • Figure 5: Dimensions of different sized boxes that are tested on the drones ranging from small to large
  • ...and 4 more figures