## 6 Experimental Methods for Evaluating HAPS Propeller Performance
The results show good agreement with those obtained from CFD. In particular, the performance trends with respect to the advance ratio observed in the CFD, although slightly underestimating the experimental values, closely matched those from the wind tunnel experiments, with an average difference of less than 1% in propeller efficiency (Figure 21). Similar agreement was also found for the thrust and power coefficient curves. Figure 21: Comparison of \(\eta\) versus \(J\) from CFD and wind tunnel measurements (\(Re_{\rm avg}~{}=~{}4\times 10^{4}\)). Black and red asterisks indicate the design points with and without Gurney flap, respectively. Figure 20: Comparison of \(C_{t}\) versus \(J\) from QPROP, CFD-AMI, CFD-FR, JBLADE, and Wind Tunnel measurements. However, in addition to the difficulty of testing large-diameter propellers, the high cost of wind tunnel experiments often limits their applicability to high-altitude propeller research. To address these limitations, recent studies have introduced alternative methodologies based on mobile testing platforms. One such approach is presented by [152], who developed an innovative experimental methodology specifically designed to evaluate the performance of propellers for HAPSs. Their work focused on characterizing the aerodynamic behavior of a 6.8 m-diameter propeller intended to operate at 20 km altitude, with a rotational speed of 500 rpm and a flight speed of 20 m/s. To this end, two mobile experimental testing systems were designed: one for testing scaled propellers under simulated high-altitude conditions, and another for testing the full-scale propeller at lower altitudes. The experimental setup consists of three core components: the test platform, the measurement and control system, and the delivery platform. For scaled tests, special attention was given to minimizing external disturbances and accurately capturing the relatively small aerodynamic forces. The test rig is mounted on a modified vehicle and elevated above the cab to maintain undisturbed flow conditions. Propellers are driven by a DC motor with a speed reducer and powered by a stabilized voltage supply. Measurement systems are adapted to the scale of the propeller. For the full-scale configuration, thrust and torque are measured using a custom dynamometer with four S-shaped load cells detecting structural deformations, and a separate axial force sensor mounted on slide rails. In contrast, the scaled system uses an inline S-shaped load cell for thrust and a rotary torque sensor for torque, both placed between the motor and the propeller to improve sensitivity. Real-time data acquisition is managed through a National Instruments cDNAQ-9188 system with multiple I/O modules, while wind conditions are recorded using an ultrasonic anemometer and a barometer. A LabVIEW-based interface controls motor operation and processes measurement data through dedicated modules for control, acquisition, and logging. Testing is conducted along straight, flat roadways to generate relative wind, although maintaining a constant vehicle speed remains a limitation. Nonetheless, the method offers a practical, low-cost alternative to wind tunnel testing for high-altitude applications. Data segments corresponding to steady-state conditions are isolated and processed using statistical filtering (3\(\sigma\) criterion) to ensure the robustness of the aerodynamic performance results. Validation of these mobile testing methods was carried out independently for each system. The full-scale 4.6 m propeller was tested at ground level under static (V = 0 m/s) and dynamic (V = 5 m/s) conditions over a speed range of 100-200 rpm. The experimental results showed good agreement with CFD predictions, especially for static thrust, with mean relative errors below 8% in dynamic conditions. Deviations at low advance ratios were primarily attributed to the small aerodynamic loads and the influence of vibrations and road irregularities.