Hybrid Analytical and Data-Driven Models for Integrated Simulation and Design of Complex High Frequency Multi-Winding Magnetic Components

用于复杂高频多绕组磁性元件集成仿真和设计的混合分析和数据驱动模型

• 批准号: 2344664
• 负责人: Minjie Chen
• 金额: $ 33.89万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2344664&HistoricalAwards=false
• 关键词: Hybrid; Analytical; Data; Driven; Models

Electrical power converters are critical to a wide range of applications from renewable integration to transportation electrification and can be a key factor in determining the size, weight, and efficiency of all types of energy conversion systems. Magnetic components are typically the largest and least efficient components in power electronics. While there have been major strides in the development of wide-bandgap (WBG) semiconductor devices and circuit topologies, the necessary advances in the modeling and design of complex power magnetic components are lagging. This project will conduct fundamental research on the magnetics modeling theory for linear and non-linear micro- and macro-scale behavior analysis of power magnetics. The linear electromagnetic field and current distribution in windings, and the non-linear hysteresis of power magnetic core materials will be modeled under a unified framework, targeting sophisticated magnetic structures with matrix coupled flux and non-uniform flux distribution. Methods will be developed to characterize the complex behavior of electromagnetic hysteresis in the magnetic materials and model the way they impact the field and current distribution in magnetic components. The outcomes of this project include 1) a systematic method for modeling and designing complex multi-winding power magnetics; 2) a family of software tools for optimal design of power magnetics; and 3) a group of design examples to demonstrate and validate the effectiveness of the new modeling approach. These outcomes will make the magnetic components in future electric vehicles, computers, renewable energy systems more compact, more efficient, and be able to perform more sophisticated functions. With the theories and methodologies developed in this project, sophisticated magnetic components can be designed and simulated with high accuracy, and fully unlock the potential of WBG devices. This will increase energy efficiency, reduce emissions, and create new societal opportunities. We will work to ensure this outcome by disseminating the results in education, research, and commercialization. There will be impact on research experiences and training of engineering students. Research will be conducted by both undergraduate and graduate students, strengthening their skills in this important area, with participation of under-represented groups especially encouraged. The outcomes of this research will be embedded into the MagNet Project – an international open-source magnetics community effort.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

电力转换器对于从可再生能源集成到运输电气的广泛应用至关重要，并且可能是确定所有类型能量转换系统的尺寸，重量和效率的关键因素。磁成分通常是电力电子中最大，最不高效的组件。尽管在宽带gap（WBG）半导体设备和电路拓扑的开发方面取得了长足的进步，但复杂功率磁性组件的建模和设计的必要进步却滞后。该项目将对磁性和非线性微型和宏观尺度行为分析功率磁体的磁性建模理论进行基础研究。线性电磁场和绕组中的电流分布以及功率磁芯材料的非线性磁滞将在统一框架下建模，靶向具有基质耦合通量和非均匀通量分布的复杂磁性结构。将开发方法来表征磁性材料中电磁滞后的复杂行为，并建模它们影响磁成分中的场和电流分布的方式。该项目的结果包括1）一种用于建模和设计复杂的多磁力磁力的系统方法； 2）用于最佳电源设计的软件工具系列； 3）一组设计示例，以证明和验证新建模方法的有效性。这些结果将使未来的电动汽车，计算机，可再生能源系统更紧凑，更高效，并能够执行更复杂的功能中的磁成分。通过在该项目中开发的理论和方法，可以以高精度设计和模拟复杂的磁性组件，并完全解锁WBG设备的潜力。这将提高能源效率，减少排放并创造新的社会机会。我们将通过传播教育，研究和商业化的结果来确保这一结果。将对工程专业学生的研究经历和培训产生影响。本科生和研究生将进行研究，并在这一重要领域加强他们的技能，特别鼓励代表性不足的群体的参与。这项研究的结果将嵌入到磁铁项目中 - 国际开源磁铁社区的努力。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，通过评估来诚实地获得支持。