Recent times have seen a tremendous increase in the development and usage of small Unmanned Aircraft Systems (sUASs) for both military and commercial applications. As the utilization of sUASs continues to increase, the design of improved propellers for these sUASs is an important area for research. The power requirements of sUASs is highly influenced by how efficiently electrical power can be turned into propulsive power. Utilizing a more efficient propeller allows a sUAS to either operate longer using the same power source or to use a smaller power source to improve the performance. A major source of inefficiency in propellers is the induced drag created by the vortices from the tip of the propeller. One potential method to reduce these vortices and increase efficiency is unloading the tip of the propeller by specifying the distribution of the lift coefficient (C_L). A common method for designing and evaluating propellers is the Blade Element Momentum Theory (BEMT). Currently, the QMIL and QPROP programs, based on BEMT, are the most frequently utilized programs for designing and creating propellers. However, QMIL and QPROP have several limitations that make them difficult to use. They utilize DOS commands which can be complicated to use on newer operating systems. These programs are limited in their ability to accurately model C_L and the drag coefficient (C_D) as a function of angle of attack (AOA), and are unable to create a propeller with a prescribed C_L distribution. Due to the limitations presented by QMIL and QPROP, an Excel based spreadsheet was created, using BEMT, to enable the design and evaluation of propellers with a prescribed C_L distribution. This program allows for rapid evaluation and comparison of potential propeller designs to enable determination of optimal designs for testing and further evaluation. The spreadsheet's accuracy is validated by testing four propellers utilizing the Clark-Y airfoil with differing amounts of the outboard portion of the propeller unloaded. Results are compared to the program's predictions in order to validate the spreadsheet as a design tool.
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Bennett et al. (2024) studied this question.
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