Abstract: In order to improve the fuzzy judgments of green evaluation weight for product schemes, a green degree evaluation method of high efficiency motor was proposed based on expected goal and Larsen-type fuzzy inference. On the basis of decomposing characteristic information of product schemes in life cycle, a hierarchical model of green degree evaluation was established. According to the minimax clustering fuzzy (max-min) principle, three factors of products such as environment properties, energy attributes, and resource attributes were considered comprehensively. Moreover, the expected goal of project was set up by designers combining with the product standard, the production status of enterprise, and the environmental characteristics, which raised the objectivity and clarity of evaluation processes. The theoretical model was verified by the example of high efficiency low voltage three-phase asynchronous motor YE3 160L-4. The results show that the motor has a further optimization space on the consumptions of mineral resources, acid oxide emissions and so on.

Key words: green degree evaluation, fuzzy inference, expected goal, product scheme, life cycle

摘要： 为改善产品方案绿色度评价权重判断模糊的问题，提出一种基于预期目标和Larsen模糊推理的高效能电机绿色度评价方法。在对产品方案生命周期特征信息分解的基础上，构建绿色度评价递阶层次模型。根据极大极小聚类模糊(max-min)原则，综合考虑产品环境属性、能源属性、资源属性三方面因素，结合设计者对产品方案标准、企业生产状况、环境特性等因素设定方案预期目标进行评价，提升了评价过程的客观性与明晰性。以高效能低压三相异步电机YE3 160L-4为例验证模型, 结果表明，它在矿产资源消耗量、酸性氧化物排放等水平上有进一步优化空间。

关键词: 绿色度评价, 模糊推理, 预期目标, 产品方案, 生命周期