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Optimization of Horizontal-Axis Turbine Blades under Drivetrain Resistance
Dara C S Araújo1, Jerson R P Vaz1, Erb F Lins2
1Universidade Federal do Pará, Programa de Pós-Graduação em Engenharia Mecânica, Av. Augusto Corrêa, 01, Guamá, 66075-900 Belém, PA, Brazil.
Anais Da Academia Brasileira De Ciencias
|June 3, 2026
Summary
This study enhances horizontal axis turbine blade design by incorporating drivetrain resistance, improving performance at low speeds. The new model optimizes blade geometry for better torque generation and energy extraction.
Area of Science:
- Renewable Energy Engineering
- Aerodynamics and Hydrodynamics
Background:
- Traditional horizontal axis turbine blade designs prioritize aerodynamic or hydrodynamic efficiency, often overlooking drivetrain resistance.
- Drivetrain resistive forces from bearings and generators significantly impact turbine performance, especially at low rotational speeds.
Purpose of the Study:
- To develop an advanced optimization model for horizontal axis turbine blades that integrates drivetrain resistive forces.
- To enhance turbine energy extraction and starting torque at low wind or water speeds.
Main Methods:
- Incorporation of drivetrain resistive forces into Glauert's optimization framework.
- Application of Blade Element Momentum Theory to maximize the power coefficient.
- Integration of resistive force coefficients into blade section velocity diagrams to determine distributed loads.
Main Results:
- The developed model yields significant variations in optimal chord distribution, leading to improved blade geometry for enhanced torque generation.
- Comparative analysis demonstrates superior energy extraction compared to Glauert's traditional model.
- A notable 16.39% increase in starting torque was observed when applying the new model.
Conclusions:
- Accounting for drivetrain resistance is crucial for optimizing turbine blade design, particularly for low-speed applications.
- The proposed model offers a more comprehensive approach to turbine blade optimization, leading to improved overall performance and efficiency.
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