【摘要】 文章针对电动自行车形态设计与用户感性需求脱节问题，构建感性需求与形态要素的量化映射模型，提升设计效率与用户满意度。搜集电动自行车样本图片和用户感性词汇，获取用户的感性意象评价，对评价数据降维处理；按照电动自行车的形态设计要素解构并编码，构建并训练BP神经网络模型，实现用户感性认知与形态设计要素之间的关联映射，指导电动自行车形态设计，通过验证对比证明模型有效，解决传统设计中主观需求与客观实现间的匹配难题。更多还原

【Abstract】 In response to the disconnection between the design of electric bicycles and users’ emotional needs, a quantifiable mapping model between emotional needs and design elements is constructed to enhance design efficiency and user satisfaction. Sample images of electric bicycles and emotional vocabulary from users are collected to obtain evaluations of users’ emotional imagery, and dimensionality reduction is performed on the evaluation data. The design elements of electric bicycles are deconstructed and encoded, and a BP neural network model is built and trained to achieve a mapping relationship between users’ emotional cognition and design elements. This will guide the design of electric bicycles. The model’s validity is demonstrated through verification and comparison, addressing the challenge of matching subjective needs with objective realizations in traditional design.更多还原