电源学报

续流二极管反向恢复电流峰值模型及其在结温预测中的应用研究

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焦乾明 , 祝令瑜 , 占草 , 刘占磊 , 王伟丞 , 汲胜昌

电源学报 | 功率半导体器件 2025,23(6): 329-339

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电源学报 |功率半导体器件 2025 , 23 (6) : 329 -339

续流二极管反向恢复电流峰值模型及其在结温预测中的应用研究

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焦乾明（1998—　），男，硕士研究生。研究方向：功率模块结温监测技术及其应用。E-mail：854074130@qq.com。

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占草（1993—　），男，博士研究生。研究方向：功率器件可靠性分析，电力电子化电力设备状态监测。E-mail：zhancao@stu.xjtu.edu.cn。

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占草（1993—　），男，博士研究生。研究方向：功率器件可靠性分析，电力电子化电力设备状态监测。E-mail：zhancao@stu.xjtu.edu.cn。

刘占磊（1998—　），男，硕士研究生。研究方向：中频变压器的设计。E-mail：2452356003@qq.com。

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刘占磊（1998—　），男，硕士研究生。研究方向：中频变压器的设计。E-mail：2452356003@qq.com。

王伟丞（1994—　），男，硕士研究生。研究方向：MMC子模块状态监测技术。E-mail：2985746736@qq.com。

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王伟丞（1994—　），男，硕士研究生。研究方向：MMC子模块状态监测技术。E-mail：2985746736@qq.com。

汲胜昌（1976—　），男，博士，教授。研究方向：电力设备状态监测及故障诊断，电力设备振动与噪声，新能源设备服役特性及状态评估。E-mail：jsc@xjtu.edu.cn。

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焦乾明, 祝令瑜, 占草, 刘占磊, 王伟丞, 汲胜昌

作者信息

西安交通大学电工材料电气绝缘全国重点实验室，西安　710049

通讯作者:

祝令瑜（1988—　），男，通信作者，博士，副教授。研究方向：电力设备振动与噪声，直流电弧特性与检测，电力设备状态监测及故障诊断，新能源设备服役特性及状态评估。E-mail：zhuly1026@xjtu.edu.cn。

作者简介:

焦乾明（1998—　），男，硕士研究生。研究方向：功率模块结温监测技术及其应用。E-mail：854074130@qq.com。

占草（1993—　），男，博士研究生。研究方向：功率器件可靠性分析，电力电子化电力设备状态监测。E-mail：zhancao@stu.xjtu.edu.cn。

刘占磊（1998—　），男，硕士研究生。研究方向：中频变压器的设计。E-mail：2452356003@qq.com。

王伟丞（1994—　），男，硕士研究生。研究方向：MMC子模块状态监测技术。E-mail：2985746736@qq.com。

Peak Reverse Recovery Current Model for Freewheeling Diode and Its Application in Junction Temperature Prediction

Qianming JIAO, Lingyu ZHU, Cao ZHAN, Zhanlei LIU, Weicheng WANG, Shengchang JI

Affiliations

State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710049, China

出版时间: 2025-10-30 doi: 10.13234/j.issn.2095-2805.2025.6.329

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摘要

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准确预测功率模块芯片结温对保证其正常可靠运行具有重要意义。目前对于续流二极管芯片结温预测的研究尚不充分，缺乏二极管的温敏电参数模型与机理研究。基于续流二极管关断过程推导二极管反向恢复电流峰值模型，建立反向恢复电流峰值与母线电压、负载电流和结温的关系。进而提出基于随机变异粒子群优化算法的反向恢复电流峰值模型参数辨识方法，利用双脉冲实验结果提取模型参数并对模型进行验证。为了避免载流子线性分布和线性变化带来的模型误差，进一步增加模型中负载电流及母线电压指数参数，实现了峰值电流预测的优化。最后基于优化后的模型提出功率模块续流二极管芯片结温预测方法，相较查表法具有更高的预测精度，满足续流二极管结温预测需求。

关键词

功率模块 / 续流二极管芯片 / 结温预测 / 反向恢复电流 / 粒子群优化算法

Abstract

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The accurate chip junction temperature prediction of power semiconductor modules is significant for their reliable operation. However, the research about freewheeling diode (FWD) chip junction temperature prediction is not sufficient at present, and the models of temperature sensitive electric parameters and the corresponding evaluation mechanism are lacking. A peak reverse recovery current model is deduced based on the turn-off process of FWD, and the relationship of peak reverse recovery current with bus voltage, load current and junction temperature is established. Then, a parameter identification approach for the peak reverse recovery current model is proposed based on the particle swarm optimization algorithm with random mutation, and the result of double-pulse test is used to extract the model parameters and verify the model. To reduce the model error caused by the linear distribution and linear changes of carriers, the exponential terms of load current and bus voltage are further added, thus optimizing the prediction of peak current. Finally, a junction temperature prediction approach for FWD chips in power semiconductor modules is put forward based on the optimized model, and this approach is more accurate compared with the look-up-table method, indicating that it can satisfy the requirements of FWD junction temperature prediction.

Key words

Power semiconductor module / freewheeling diode (FWD) chip / junction temperature prediction / reverse recovery current / particle swarm optimization algorithm

引用本文

焦乾明, 祝令瑜, 占草, 刘占磊, 王伟丞, 汲胜昌. 续流二极管反向恢复电流峰值模型及其在结温预测中的应用研究. 电源学报, 2025 , 23 (6) : 329 -339 . DOI: 10.13234/j.issn.2095-2805.2025.6.329

Qianming JIAO, Lingyu ZHU, Cao ZHAN, Zhanlei LIU, Weicheng WANG, Shengchang JI. Peak Reverse Recovery Current Model for Freewheeling Diode and Its Application in Junction Temperature Prediction[J]. Journal of Power Supply, 2025 , 23 (6) : 329 -339 . DOI: 10.13234/j.issn.2095-2805.2025.6.329

基金

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国家自然科学基金资助项目(51877168)

参考文献

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2025年第23卷第6期

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文章信息

doi: 10.13234/j.issn.2095-2805.2025.6.329

接收时间：2022-09-15
首发时间：2026-10-26
出版时间：2025-10-30

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收稿日期：2022-09-15
修回日期：2023-03-17
录用日期：2023-03-31

基金

National Natural Science Foundation of China(51877168)

国家自然科学基金资助项目(51877168)

作者信息

西安交通大学电工材料电气绝缘全国重点实验室，西安　710049

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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