跨学科开关电源中磁性元件材料设计技能的评估和持续改进

IF 0.7 4区 材料科学 Q3 Materials Science Materials Express Pub Date : 2024-01-01 DOI:10.1166/mex.2024.2581
Yi Kuang, Zhiyong Zhang, Bin Duan
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引用次数: 0

摘要

开关模式电源(SMPS)的设计是一个材料-电气工程跨学科问题。磁性元件材料的设计会极大地影响 SMPS 的性能。在工程教育中,设计和开发解决方案是工科学生的一项重要技能。然而,传统的工程实验课程表现为验证性、单一学科实验以及片面的考核结果。要培养学生的开放式探索精神,增强学生的材料设计能力,提高技能适应性,就必须让学生解决实际工程问题,开发出切实可行的设计方案。本文结合 SMPS 设计任务,提出了基于探索性因子分析和知识图谱的磁性元件材料设计技能评价与持续改进方法。首先,我们使用多重归因法解决数据缺失问题。通过平行分析、普通最小二乘估计和目标旋转,对每个归因数据进行分析,提取因子。然后,我们确定了四个子技能:效率设计技能、无源器件设计技能、功率磁性降低设计技能和功率经济性设计技能。四因子模型的均方根误差为 0.042,表明与数据拟合良好。我们确定了这些子技能与 SMPS 性能指标之间的关系。此外,我们将每个估算数据集的因子得分平均值与 SMPS 设计限制条件相结合,得出了评估工科学生在这些子技能方面成绩的临界分数。最后,我们构建了 SMPS 磁性元件材料知识图谱,该图谱可推荐具体的实验任务、相关知识领域和 SMPS 性能指标,为设计者提供个性化指导。
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Evaluation and continuous improvement of magnetic components material design skills in interdisciplinary switched-mode power supply
The design of switched-mode power supplies (SMPSs) is a material-electrical engineering interdisciplinary problem. The design of magnetic component materials can significantly affect SMPSs’ performances. In engineering education, the design and development of solutions is an important skill for engineering students. However, the traditional engineering experiments curriculum is shown as validation and single-disciplinary experiments as well as one-sided assessment results. To foster open-ended exploration, enhance students’ material design skills, and improve skills adaptation, students must tackle real engineering problems and develop practical design solutions. This paper proposes an exploratory factor analysis and knowledge graph-based method for evaluating and continuously improving magnetic components material design skills in the context of SMPS design tasks. First, we used the multiple imputation method to address the missing data. Each imputed data was analyzed to extract factors through parallel analysis, ordinary least squares estimation, and target rotation. Then, we identified four sub-skills: efficiency design skill, passive device design skill, power magnetic reduction design skill, and power economy design skill. The RMSEA for the four-factor model is 0.042, suggesting a good fit to the data. We established the relationships between these sub-skills and SMPS performance metrics. Furthermore, the average of the factor scores from each of the imputed datasets and the SMPS design constraints were combined to obtain the cut-off scores to evaluate engineering students’ achievements in these sub-skills. Finally, we constructed an SMPS magnetic components material knowledge graph, which could recommend specific experimental tasks, relevant knowledge areas, and SMPS performance metrics, providing personalized guidance to designers.
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来源期刊
Materials Express
Materials Express NANOSCIENCE & NANOTECHNOLOGY-MATERIALS SCIENCE, MULTIDISCIPLINARY
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0.00%
发文量
69
审稿时长
>12 weeks
期刊介绍: Information not localized
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