Abstract: Modular multi-array fan wind tunnel technology represents a transformative advancement in experimental aerodynamics, overcoming fundamental limitations of traditional wind tunnels in structural rigidity, energy consumption, and flow-field reconfigurability. This innovation leverages high-density, independently controllable fan arrays to dynamically manipulate the flow field, enabling unprecedented dynamic control over wind speed, direction, and crucially, unsteady flow characteristics like turbulence. Consequently, this significantly enhances flow-field uniformity, spatiotemporal response, and terrain wind speed profile reproduction, establishing thistechnology as vital for aerospace, UAV testing, and urban microclimate studies. Current research focuses on optimizing distributed fan structures and modular design, managing inherent aerodynamic coupling, and developing intelligent control systems employing CFD, AI optimization, and real-time feedback. However, significant challenges persist concerning nonlinear hysteresis effects, large-section flow-field uniformity, and high-dynamic turbulence reconstruction; addressing these necessitates breakthroughs in multi-source sensing and intelligent control algorithms. Driven by diverse applications, the technology's evolution consequently moves towards deeper AI integration and synergy with digital twins. Future developments will leverage AI/ML, high-resolution sensing, and distributed control to achieve high-precision testing under extreme conditions while expanding into structural safety and environmental domains.