Abstract: Focusing on the requirement analysis and affective design of smart cockpit for intelligent connected vehicles (ICV) , an effective method was proposed to optimize the system function configuration to enhance the user's affective experience, and a “usage-comment-psychology” Kansei engineering analysis framework was proposed by incorporating the web comment data and behavioral log data generated by users to extract the characteristics of the psycholinguistic demand. The proposed Kansei engineering analysis framework adopted multimodal data and combined large language models with econometric models. Through incremental pre-training of large language model, three types of comment demand feature labels, namely, the application type, the comment intention, and the sentiment polarity, were predicted with 95.22% accuracy. Together with the psycholinguistic features derived from TextMind and the usage behavior features, they were incorporated into the structural equation model. The model expanded the scope of the analysis of requirements engineering, and to further explain the user’s affective requirements for the smart cockpit. As an application example, the behavior of 2,048 ICV drivers were tracked for four months. The results verified the effectiveness of the method in revealing users’ application requirements and sentiment tendencies. Compared with the linear regression model and the “usage-comment” structural equation model, the “usage-comment-psychology” model had a better goodness-of-fit and further revealed the implicit relationship between behavior and psycholinguistic features. Driven by the user big data, the method realized automatic extraction and relationship interpretation of multiple dimensional features such as behavior, opinion and psychology, which provided a feasible solution for revealing the mechanism between users’ complex behaviors and design requirements. It also provided a valuable reference for manufacturing enterprises to understand customers’ requirements and iterate the direction of their products.