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Wing Optimisation for a tractor propeller driven Micro Aerial Vehicle

Arjun Sharma, Roddam Narasimha

TL;DR

This work adapts a tractor-propeller wing-optimization framework to a small MAV (Avion) to quantify potential drag and endurance gains from wing planform and twist adjustments under propwash. By combining OpenFOAM-based slipstream computation with lifting-line theory and empirical aerofoil data, the authors demonstrate that allowing a modest variation in the operating lift coefficient can unlock meaningful endurance improvements (up to ~18.6% for ±10% CL and up to ~39.2% for ±50% CL). The results show that viscous drag reductions from the E423 laminar bucket are pivotal, and that optimized designs tend to reduce chords behind the propeller while increasing outboard twist, albeit with potential tip-stall risk. The study validates the methodology with propeller benchmarks and 2D-PIV slipstream data, offering practical directions for MAV wing design and future, higher-fidelity validation.

Abstract

This paper describes an investigation of the possible benefits from wing optimisation in improving the performance of Micro Air Vehicles (MAVs). As an example we study the Avion (3.64 kg mass, 1.60 m span), being designed at the CSIR National Aerospace Laboratories (NAL), Bengaluru. The optimisation is first carried out using the methodology described by Rakshith \emph{et al.} (using an in\textendash house software PROWING), developed for large transport aircraft, with certain modifications to adapt the code to the special features of the MAV. The chief among such features is the use of low Reynolds number aerofoils with significantly different aerodynamic characteristics on a small MAV. These characteristics are taken from test data when available, and/or estimated by the XFOIL code of Drela. A total of 8 optimisation cases are studied for the purpose, leading to 6 different options for new wing planforms (and associated twist distributions along the wing span) with an improved performance. It is found that the improvements in drag coefficient using the PROWING code are about 5%. However, by allowing the operating lift coefficient $C_L$ to float within a specified range, drag bucket characteristics of the Eppler E423 aerofoil used on Avion can be exploited to improve the endurance, which is a major performance parameter for Avion. Thus, compared to the control wing $W_0$ (with operating point at $C_L$ =0.7) used in the preliminary design, permitting a variation of $C_L$ over a range of $\pm$ 10% is shown to enhance the endurance of wing $W_4$ by 18.6%, and of wing $W_{6}$ with a permitted $C_L$ range of $\pm$ 50% by 39.2%. Apart from the philosophy of seeking optimal operating conditions for a given configuration, the advantages of optimising design parameters such as washout of a simple wing proposed in the preliminary design stage, is also demonstrated.

Wing Optimisation for a tractor propeller driven Micro Aerial Vehicle

TL;DR

This work adapts a tractor-propeller wing-optimization framework to a small MAV (Avion) to quantify potential drag and endurance gains from wing planform and twist adjustments under propwash. By combining OpenFOAM-based slipstream computation with lifting-line theory and empirical aerofoil data, the authors demonstrate that allowing a modest variation in the operating lift coefficient can unlock meaningful endurance improvements (up to ~18.6% for ±10% CL and up to ~39.2% for ±50% CL). The results show that viscous drag reductions from the E423 laminar bucket are pivotal, and that optimized designs tend to reduce chords behind the propeller while increasing outboard twist, albeit with potential tip-stall risk. The study validates the methodology with propeller benchmarks and 2D-PIV slipstream data, offering practical directions for MAV wing design and future, higher-fidelity validation.

Abstract

This paper describes an investigation of the possible benefits from wing optimisation in improving the performance of Micro Air Vehicles (MAVs). As an example we study the Avion (3.64 kg mass, 1.60 m span), being designed at the CSIR National Aerospace Laboratories (NAL), Bengaluru. The optimisation is first carried out using the methodology described by Rakshith \emph{et al.} (using an in\textendash house software PROWING), developed for large transport aircraft, with certain modifications to adapt the code to the special features of the MAV. The chief among such features is the use of low Reynolds number aerofoils with significantly different aerodynamic characteristics on a small MAV. These characteristics are taken from test data when available, and/or estimated by the XFOIL code of Drela. A total of 8 optimisation cases are studied for the purpose, leading to 6 different options for new wing planforms (and associated twist distributions along the wing span) with an improved performance. It is found that the improvements in drag coefficient using the PROWING code are about 5%. However, by allowing the operating lift coefficient to float within a specified range, drag bucket characteristics of the Eppler E423 aerofoil used on Avion can be exploited to improve the endurance, which is a major performance parameter for Avion. Thus, compared to the control wing (with operating point at =0.7) used in the preliminary design, permitting a variation of over a range of 10% is shown to enhance the endurance of wing by 18.6%, and of wing with a permitted range of 50% by 39.2%. Apart from the philosophy of seeking optimal operating conditions for a given configuration, the advantages of optimising design parameters such as washout of a simple wing proposed in the preliminary design stage, is also demonstrated.
Paper Structure (25 sections, 10 equations, 14 figures, 3 tables)

This paper contains 25 sections, 10 equations, 14 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Propeller Performance Parameters
  3. Validation of computational procedure proposed
  4. Deters' propeller– DA4002
  5. NACA Propeller
  6. Experimental Data: 2D PIV
  7. Avion control characteristics
  8. Aerofoil Characteristics
  9. Wing Characteristics
  10. Optimisation Methodology and Results
  11. Approach 1: Fixed Wing Lift coefficient ($C_L=0.7$)
  12. $C_{D_{i}}$ Optimisation:
  13. $C_{D}$ Optimisation:
  14. Approach 2: Floating $C_L$ within a specific range
  15. Up to 10% change in $C_L$ allowed:
  16. ...and 10 more sections

Figures (14)

  • Figure 1: Experimental Deters2014 and computational (OpenFoam Incompressible Euler) thrust coefficient for DA4002
  • Figure 2: Experimental Hartman1938 and computational (OpenFoam Incompressible Euler) thrust coefficient for NACA propeller
  • Figure 3: APC 11$\times$7 thin electric propeller slip– stream velocity one diameter downstream of the propeller plane.
  • Figure 4: Initial Configuration of Avion NAL_Personal
  • Figure 5: E423 aerofoil geometry
  • ...and 9 more figures