What question did this study set out to answer?

The aim is to optimize the design of an axial-flow automotive fan for better efficiency, pressure, and flow characteristics.

March 1, 2026ACS OmegaOpen Access

Pareto-Driven Multiobjective Design of Axial-Flow Automotive Fan with Response Surface Modeling

View Full Paper

Ask AI

Bookmark

Authors

Multiobjective optimization improves efficiency and pressure in axial-flow automotive fans, suggesting a novel design strategy.

The aim is to optimize the design of an axial-flow automotive fan for better efficiency, pressure, and flow characteristics.
Utilized response surface methodology and genetic algorithms for optimization.
Optimized four parameters: root and tip installation angles, and sweep angles.
Conducted sensitivity analysis to assess parameter impacts on performance.
Used 25 Latin Hypercube Sampling points to create a surrogate model.
Achieved a high accuracy surrogate model with R2 > 0.99.
Improved efficiency from 18.31% to 21.19% while maintaining flow and pressure levels.
Identified that tip angle significantly affects volumetric flow rate and static pressure, while root angle impacts efficiency.
Demonstrated enhanced aerodynamic stability with smoother velocity profiles and reduced separation areas.

Ren et al. (2026) studied this question.

View Full Paper

Ask AI

Bookmark