Using entropy weight method and quality function deployment to develop emotion-driven dashboard interfaces for NEV

New energy vehicles (NEVs) demand dashboard interfaces that not only present critical driving information but also evoke positive user emotions to enhance satisfaction and safety. This study develops a structured framework that integrates the Entropy Weight Method (EWM) and Quality Function Deployment (QFD) to embed emotion-driven requirements into NEV dashboard design. 56 Kansei words were collected through an online survey (n = 300) and prioritized to 15 through experts interviews. An anonymous online questionnaire (n = 101, 98 valid responses) collected adult drivers' emotional perceptions across 15 descriptive adjectives. Exploratory factor analysis distilled these descriptors into four principal dimensions: Pleasant, Technological, Stylish, and Minimalist. Entropy weight calculation quantified the relative importance of each dimension, revealing Pleasantness as the highest-priority factor. The QFD process then translated these weighted emotional dimensions into specific design attributes, including optimal color contrast ratios, iconography style guidelines, typography choices, and interface layout coherence. Prototype dashboards developed according to this schema were evaluated in a pilot study, demonstrating strong congruence between user-prioritized emotions and perceived design quality. This framework offers a replicable, data-driven method for systematically aligning emotional user needs with interface design parameters in NEVs, thereby providing actionable guidance for designers aiming to improve user experience through emotion-driven dashboard development.