To mitigate aviation accidents attributable to human factors, this study develops an affective evaluation method for aircraft cockpit interiors in complex dynamic environments. A simplified model was constructed along the dimensions of mission timeline, phase, and scenario, and a Comprehensive Impact Index of Complex Dynamic Environments on Flight Emotions was defined. Criteria and method for pilot perceptual measurement were subsequently established. Following this, perceptible design features were characterized through flight simulation experiments replicating complex dynamic conditions, enabling collection of pilots' subjective and objective perceptual data. A BP neural network-based predictive model for cockpit interior evaluation was developed and validated. This work provides an evaluation methodology and experimental paradigm that better reflects real flight conditions, contributing to enhanced perceptual interaction in cockpit environments and supporting aviation safety.