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功率模块多物理场快速求解技术综述

祝令瑜 唐义政 占草 康子章 王伟丞 汲胜昌

高电压技术2025,Vol.51Issue(10):4881-4899,19.
高电压技术2025,Vol.51Issue(10):4881-4899,19.DOI:10.13336/j.1003-6520.hve.20250369

功率模块多物理场快速求解技术综述

Review of Fast Solution Techniques for Multi-physics Fields in Power Modules

祝令瑜 1唐义政 1占草 2康子章 1王伟丞 1汲胜昌1

作者信息

  • 1. 电工材料电气绝缘全国重点实验室(西安交通大学),西安 710049
  • 2. 弗吉尼亚理工大学电力电子系统研究中心,弗吉尼亚州布莱克斯堡24061
  • 折叠

摘要

Abstract

As a core component of power conversion systems,the reliability of power modules directly determines the safety and stability of systems such as renewable energy generation and high-voltage direct current(HVDC)transmission.Multi-physics modeling and analysis are essential for revealing the operating states and degradation mechanisms of power modules.However,traditional numerical methods face computational efficiency bottlenecks,making it challenging to meet the real-time condition monitoring and intelligent diagnostic requirements of modern power systems.Therefore,this paper summarizes the packaging forms and multi-physics modeling methods of bond-wire and press-pack power modules.Tthe research progress in fast solution techniques for power modules is reviewed,focusing on model order reduction,projection-based reduction,and deep learning-based reduction methods.Moreover,this paper also discusses the local re-duction methods for multi-physics coupled models and provides a comparative analysis of the advantages and disadvantages of various fast solution methods.Based on these discussions,this paper further explores the urgent research areas,offering significant reference value for advancing multi-physics fast solution methods,digital twins,and smart op-eration and maintenance.

关键词

功率模块/多物理场耦合/快速求解/物理模型降阶/投影降阶/深度学习

Key words

power module/multi-physics coupling/fast solution/physical model order reduction/projection-based re-duction/deep learning

引用本文复制引用

祝令瑜,唐义政,占草,康子章,王伟丞,汲胜昌..功率模块多物理场快速求解技术综述[J].高电压技术,2025,51(10):4881-4899,19.

基金项目

国家重点研发计划(2023YFB2406900).Project supported by National Key R&D Program of China(2023YFB2406900). (2023YFB2406900)

高电压技术

OA北大核心

1003-6520

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