Against the backdrop of rapid iteration in intelligent electric vehicles, design language has emerged as a core carrier for brand identification and user emotional interaction. However, the dynamic coupling between design language and users' perceptual cognition lacks large-scale data support and objective quantitative tools. Taking BYD and Tesla as typical Eastern-Western comparative cases, this study constructs a 2020—2026 multimodal dataset consisting of 125 standardized vehicle images and 6 596 valid user comments, generating over 140 000 image-text pairs. With image-text features extracted via Chinese-CLIP, combined with Kansei engineering factor analysis and Analytic Hierarchy Process (AHP), this paper quantitatively analyzes the temporal evolution of design language and the trend of perceptual imagery matching. The results reveal obvious brand divergence in users' perceptual vocabulary: BYD is dominated by “stability” and “spaciousness”, while Tesla centers on “technological sense” and “futuristic sense”. The image-text matching degree of both brands declines slowly, with a sharper drop for Tesla, indicating diversified user aesthetics amid market maturity. At the factor level, BYD shows differentiated factor trends: its perception of technological futurism continuously weakens, whereas the imagery of luxury and refinement rebounds after bottoming out. Tesla's “technological futurism” factor remains high yet fluctuates, uncovering distinct evolutionary logics between Eastern and Western automotive brands.