Variable Pitch Propeller: Multi-Objective Optimization Design and Performance Analysis

Considering the principles of green and low-carbon development, practitioners strive to continuously improve propeller performance as a primary goal for propeller-powered aircraft. Specially, medium and high-altitude UAVs require propellers that possess sufficient thrust and high efficiency across the entire flight envelope to improve the UAV’s endurance and mission capability. However, given the constraints imposed by flight altitude, speed, and power system capacity, attaining optimal matching of rotational speed and torque for fixed-pitch propellers across different operating scenarios remains a significant challenge. To ensure optimal aerodynamic performance across diverse design points, variable pitch technology is adopted, and a multi-objective propeller optimization design method is proposed that adapts to the varying pitch angle strategy. Based on the standard strip analysis, with different profile chord lengths and twist angle distributions of the propeller blade as the control parameters, we establish a multi-objective propeller aerodynamic shape optimization model using a genetic optimization algorithm. The newly designed electrically variable pitch propeller, employing this method, exhibits good aerodynamic performance throughout the flight envelope. Its design has been validated through high-precision CFD analysis and wind tunnel testing, achieving a cruising efficiency of up to 84.5%. The results show that the propeller performance calculation has good consistency with the test and can meet the requirements of unmanned aircraft.

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Publication Details

Published
2025-02-26
DOI
https://doi.org/10.3390/engproc2024080036
Citations
1
Primary Topic
Cavitation Phenomena in Pumps
Type
article
Field-Weighted Citation Impact
0.86
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article

Variable Pitch Propeller: Multi-Objective Optimization Design and Performance Analysis

Pengcheng Du, Junbo Zhao, Yudong Zhang, Zijun Zhang et al.
1 citations
Cavitation Phenomena in Pumps
0.86
article

Variable Pitch Propeller: Multi-Objective Optimization Design and Performance Analysis

Pengcheng Du, Junbo Zhao, Yudong Zhang, Zijun Zhang, Jingbo Yu
article en
1 citations

Abstract

Considering the principles of green and low-carbon development, practitioners strive to continuously improve propeller performance as a primary goal for propeller-powered aircraft. Specially, medium and high-altitude UAVs require propellers that possess sufficient thrust and high efficiency across the entire flight envelope to improve the UAV’s endurance and mission capability. However, given the constraints imposed by flight altitude, speed, and power system capacity, attaining optimal matching of rotational speed and torque for fixed-pitch propellers across different operating scenarios remains a significant challenge. To ensure optimal aerodynamic performance across diverse design points, variable pitch technology is adopted, and a multi-objective propeller optimization design method is proposed that adapts to the varying pitch angle strategy. Based on the standard strip analysis, with different profile chord lengths and twist angle distributions of the propeller blade as the control parameters, we establish a multi-objective propeller aerodynamic shape optimization model using a genetic optimization algorithm. The newly designed electrically variable pitch propeller, employing this method, exhibits good aerodynamic performance throughout the flight envelope. Its design has been validated through high-precision CFD analysis and wind tunnel testing, achieving a cruising efficiency of up to 84.5%. The results show that the propeller performance calculation has good consistency with the test and can meet the requirements of unmanned aircraft.

China Aerodynamics Research and Development Center (CN), Beihang University (CN)
Affordable and clean energy
Openalex Percentile: Top 34%
Cavitation Phenomena in Pumps
0.86
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Variable Pitch Propeller: Multi-Objective Optimization Design and Performance Analysis — Pengcheng Du, Junbo Zhao, et al. · (2025) | TGRS Research Map | TGRS