A Rough-Set-Driven Kansei Design Method for Hybrid Electric Vehicle Front Faces Under Cultural Semantic Constraints

Hybrid electric vehicle (HEV) front-face styling is jointly constrained by functional requirements for engine intake, radiator cooling, and thermal management and by demands for brand identity and emotional expression. Existing Kansei engineering studies have largely focused on whole-vehicle exteriors or generic electrified vehicles, paying insufficient attention to the functional boundaries of HEV front grilles. Moreover, culturally informed automotive styling often relies on designers’ subjective associations and lacks a coherent design pathway. To address these gaps, this study proposes a rough-set-driven Kansei design method for HEV front faces under cultural-semantic constraints. First, an entropy-weighted neighborhood rough-set method is used to identify key Kansei requirements. A rough-set-induced hybrid-kernel prediction model is then constructed by combining rough-set indiscernibility relations with nonlinear similarity, thereby mapping discrete front-face morphological features to users’ Kansei evaluations and predicting the performance of different morphological combinations. Finally, the resulting design knowledge is integrated with the structural characteristics of traditional motifs to generate culturally oriented front-face concepts. Results identified power, premium quality, and approachability as the three key Kansei requirements for HEV front faces. The proposed rough-set-induced hybrid-kernel support vector regression (RSIHK-SVR) model achieved a mean coefficient of determination (R2) of 0.927 and a root mean square error (RMSE) of 0.157 on the test set. Compared with the optimized standard radial basis function (RBF) kernel models and the single rough-set-induced-kernel model, RSIHK-SVR achieved the highest predictive accuracy on the test set (R2 = 0.927, RMSE = 0.157), improving R2 by 0.8–13.3% and reducing RMSE by 3.1–35.9% across the comparator models, thereby confirming the effectiveness of the hybrid-kernel strategy. The model-predicted morphological configurations were then integrated with the structural characteristics of bronze animal-mask, ice-crackle lattice, and fangsheng motifs to develop three front-face concepts targeting power, premium quality, and approachability, respectively. User evaluations further showed that all three concepts effectively communicated their intended Kansei semantics and exhibited favorable cultural-semantic compatibility. The proposed method thus provides quantitative decision support for conceptual HEV front-face designs with cultural identity and differentiated styling.