High-efficiency Axial Flow Fan Design by Combining Through-flow Modeling, Optimization Algorithm and Computational Fluid Dynamics Simulation

In this study, a high-efficiency axial fan design method and process are proposed by integrating the controlled blading design (CBD) method for the spanwise design of blade angles, the through-flow analysis method incorporating three-dimensional flow effects for performance prediction of the designed fan, and an optimization algorithm suitable for multi-variable problems. The main objective of this study is to obtain the optimal spanwise distribution of blade angles and chord length. To achieve this, the three-dimensional blade design process of the axial flow fan is established using the CBD model, in which the camber angle and setting angle along the spanwise direction are set as design variables, while the chord length along the spanwise direction is considered as another design variable. To predict the performance and efficiency of the designed fan, the through-flow analysis method is introduced, and the accuracy of flow and performance predictions using this method is verified by comparing with measurement results. A newly developed hybrid metaheuristic algorithm is applied as an optimization technique in the fan design and through-flow analysis program, enabling the optimal design of a high-efficiency axial flow fan. An optimization problem maximizing fan efficiency is defined and several design constraints are also set. The optimization algorithm is applied to the fan design and through-flow analysis program, achieving a very fast and simple optimization process and obtaining the optimal axial fan model. By comparing the optimal fan model with the initial fan model based on the free-vortex flow type, it is confirmed that fan efficiency is improved by 4.2 percentage points through this optimization. To verify the reliability of this optimization design method, CFD analysis, manufacturing, and testing are conducted for the optimized fan model. A comparison between the optimal design results and CFD calculation results demonstrates that this optimization method has very high predictive accuracy and design reliability. Furthermore, by comparing the design and CFD results of the optimized model with actual performance test results, the improvement in performance and efficiency through this optimization design method is validated. Additionally, the optimized axial fan derived in this study exhibits excellent performance characteristics, maintaining high efficiency and low power characteristics even under low flow conditions.