Integrating Kansei Engineering and AI-Generated Image for Commercial Vehicle Body Morphology Design

Symmetry in vehicle body morphology is a crucial factor for achieving visual sensory balance in users, and it also serves as an important method for enhancing the efficiency of vehicle body research and development.This study proposes an AHP-SD-TOPSIS-AIGC integrated morphological design method to address multi-factorial design complexities in new energy commercial vehicle body styling under emotion-driven frameworks. Through literature retrieval and survey analysis, a Kansei evaluation system was constructed, with hierarchical design indicators established via Analytic Hierarchy Process (AHP) and weights determined through consistency matrices. TOPSIS identified optimal style forms exhibiting high emotional intention coupling, while edge detection algorithms extracted symmetrical spline features for body contour modeling. AIGC tools subsequently generated innovative solutions, validated through truck design applications to confirm method rationality and effectiveness. Results demonstrate precise alignment of styling elements with user preferences and targeted improvement identification, extendable to bus-type vehicles for multi-intention emotional design adaptation.