Article(id=1154040963430342953, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1154040955071095059, articleNumber=null, orderNo=null, doi=10.13234/j.issn.2095-2805.2024.1.171, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1612800000000, receivedDateStr=2021-02-09, revisedDate=1613404800000, revisedDateStr=2021-02-16, acceptedDate=1625500800000, acceptedDateStr=2021-07-06, onlineDate=1753074406725, onlineDateStr=2025-07-21, pubDate=1706544000000, pubDateStr=2024-01-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753074406725, onlineIssueDateStr=2025-07-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753074406725, creator=13701087609, updateTime=1753074406725, updator=13701087609, issue=Issue{id=1154040955071095059, tenantId=1146029695717560320, journalId=1146031654075715584, year='2024', volume='22', issue='1', pageStart='1', pageEnd='235', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753074404733, creator=13701087609, updateTime=1753781011721, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1157004679654760494, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1154040955071095059, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1157004679654760495, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1154040955071095059, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=171, endPage=178, ext={EN=ArticleExt(id=1154040964416004396, articleId=1154040963430342953, tenantId=1146029695717560320, journalId=1146031654075715584, language=EN, title=Adaptive Online Update Method for Thermal Model of SSPC Power Device Considering Aging Effects, columnId=1153024086025429058, journalTitle=Journal of Power Supply, columnName=Power Semiconductor Devices, runingTitle=null, highlight=null, articleAbstract=

The junction temperature monitoring of power devices in a solid-state power controller(SSPC) plays a vital role in the SSPC reliability. The thermal model method is widely used owing to its contactless measurement and simplicity. However, the aging of the power chip will lead to the degradation of the thermal path, and the junction-to-case thermal resistance of the device will increase. As a result, the actual junction temperature may far exceed the value estimated by the thermal network model, leading to an optimistic estimation of the device's state-of-health. The failure of the solder layer is considered to be one of the main reasons for the aging failure of SSPC power devices. In this paper, the device's aging state is monitored in real time during the life of SSPC, and the thermal model of the power device is adaptively updated online. The thermal impedance taken as an update basis is calculated by measuring the temperature-sensitive electrical parameters which are not affected by the degradation of the solder layer, and the thermal impedance information is associated with the aging state of the solder layer to update the thermal model. Using the proposed method, the thermal model can be updated in real time without affecting the normal operation of SSPC, and experimental results verified the effectiveness of this method.

, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Yetong QIAN, Li WANG, Ruibo ZHAO), CN=ArticleExt(id=1154041034993557586, articleId=1154040963430342953, tenantId=1146029695717560320, journalId=1146031654075715584, language=CN, title=考虑老化影响的SSPC 功率管热模型自适应在线修正方法, columnId=1153024086184812611, journalTitle=电源学报, columnName=功率半导体器件, runingTitle=null, highlight=null, articleAbstract=

固态功率控制器 SSPC(solid-state power controller)中功率管的结温监测对SSPC的可靠性有至关重要的作用,热模型法因其无需直接接触测量且方法简单而被广泛使用。然而,功率芯片的老化会导致热路径的退化,器件的结壳热阻抗增加,使实际结温远远超过热网络模型的估计值,导致对器件健康状态的乐观估计。焊料层疲劳失效被认为是SSPC 功率管老化失效的主要原因之一。因此,在 SSPC的寿命周期中实时监测器件的老化状态,并对功率管的热模型进行自适应在线修正,通过测量不受焊料层退化影响的热敏参数来计算热阻作为更新依据,将热阻信息关联焊料层老化状态来更新热模型。所提方法可在不影响 SSPC 正常工作的前提下,实时修正热模型,实验结果验证了方法的有效性。

, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=IVIH/zRAk+Yon17uEVvUsg==, magXml=daWzQGkmKP67DvW3rBgdtw==, pdfUrl=null, pdf=LOq7zCHL1vcinf9GaWMqEQ==, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=9cpzAfPvr4JQu9gQdZjU4A==, mapNumber=null, authorCompany=null, fund=null, authors=

钱叶彤(1997-),女,硕士研究生。研究方向:固态功率控制器的可靠性及热管理。E-mail:qianyt@nuaa.edu.cn。

王莉(1969-),女,通信作者,博士。研究方向:飞行器电源系统分析设计、固态配电技术、高频电力电子、故障诊断。E-mail: liwnag@nuaa.edu.cn。

赵瑞博(1994-),男,硕士研究生。研究方向:固态配电技术。E-mail: zrb@nuaa.edu.cn。

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钱叶彤(1997-),女,硕士研究生。研究方向:固态功率控制器的可靠性及热管理。E-mail:qianyt@nuaa.edu.cn。

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钱叶彤(1997-),女,硕士研究生。研究方向:固态功率控制器的可靠性及热管理。E-mail:qianyt@nuaa.edu.cn。

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王莉(1969-),女,通信作者,博士。研究方向:飞行器电源系统分析设计、固态配电技术、高频电力电子、故障诊断。E-mail: liwnag@nuaa.edu.cn。

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王莉(1969-),女,通信作者,博士。研究方向:飞行器电源系统分析设计、固态配电技术、高频电力电子、故障诊断。E-mail: liwnag@nuaa.edu.cn。

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赵瑞博(1994-),男,硕士研究生。研究方向:固态配电技术。E-mail: zrb@nuaa.edu.cn。

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赵瑞博(1994-),男,硕士研究生。研究方向:固态配电技术。E-mail: zrb@nuaa.edu.cn。

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Journal of Power Supply, 2016. 14(6): 122-135 (in Chinese)., articleTitle=Review of accelerat-ed aging methods for IGBT power modules, refAbstract=null)], funds=[Fund(id=1154041040974635217, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1154040963430342953, awardId=51777092, language=EN, fundingSource=National Natural Science Foundation of China(51777092), fundOrder=null, country=null), Fund(id=1154041041041744082, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1154040963430342953, awardId=51777092, language=CN, fundingSource=国家自然科学基金资助项目(51777092), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1154041036100853862, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1154040963430342953, xref=null, ext=[AuthorCompanyExt(id=1154041036105048167, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1154040963430342953, companyId=1154041036100853862, language=EN, country=null, 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journalId=1146031654075715584, articleId=1154040963430342953, language=EN, label=Tab. 1, caption=Material parameters of solder layer and cracks, figureFileSmall=null, figureFileBig=null, tableContent=
材料 导热率/$\left({\mathrm{W}\cdot {\left(\mathrm{m}\cdot {}^{\circ }\mathrm{C}\right)}^{-1}}\right)$ 密度/$\left({\mathrm{{kg}}\cdot {\mathrm{m}}^{-3}}\right)$ 比热容/$\left({\mathrm{J}\cdot {\left(\mathrm{{kg}}\cdot {}^{\circ }\mathrm{C}\right)}^{-1}}\right)$
焊料层 32.3 2400 300
空洞 1.0 2340 820
), ArticleFig(id=1154041040483901642, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1154040963430342953, language=CN, label=表1, caption=焊料层和空洞的材料参数, figureFileSmall=null, figureFileBig=null, tableContent=
材料 导热率/$\left({\mathrm{W}\cdot {\left(\mathrm{m}\cdot {}^{\circ }\mathrm{C}\right)}^{-1}}\right)$ 密度/$\left({\mathrm{{kg}}\cdot {\mathrm{m}}^{-3}}\right)$ 比热容/$\left({\mathrm{J}\cdot {\left(\mathrm{{kg}}\cdot {}^{\circ }\mathrm{C}\right)}^{-1}}\right)$
焊料层 32.3 2400 300
空洞 1.0 2340 820
), ArticleFig(id=1154041040592953548, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1154040963430342953, language=EN, label=Tab. 2, caption=Parameters values before and after thermal model update, figureFileSmall=null, figureFileBig=null, tableContent=
参数 原始值 更新值
${R}_{1}/\left({\mathrm{℃}\cdot {\mathrm{W}}^{-1}}\right)$ 0.01001 0.01201
${R}_{2}/\left({{}^{\circ }\mathrm{C}\cdot {\mathrm{W}}^{-1}}\right)$ 0.06594 0.07913
${R}_{3}/\left({\mathrm{C}\cdot {\mathrm{W}}^{-1}}\right)$ 0.16820 0.20184
), ArticleFig(id=1154041040681033934, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1154040963430342953, language=CN, label=表2, caption=热模型修正前后的参数值, figureFileSmall=null, figureFileBig=null, tableContent=
参数 原始值 更新值
${R}_{1}/\left({\mathrm{℃}\cdot {\mathrm{W}}^{-1}}\right)$ 0.01001 0.01201
${R}_{2}/\left({{}^{\circ }\mathrm{C}\cdot {\mathrm{W}}^{-1}}\right)$ 0.06594 0.07913
${R}_{3}/\left({\mathrm{C}\cdot {\mathrm{W}}^{-1}}\right)$ 0.16820 0.20184
), ArticleFig(id=1154041040743948495, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1154040963430342953, language=EN, label=Tab. 3, caption=Comparison of junction temperature errors before and after SSPC thermal model parameter update, figureFileSmall=null, figureFileBig=null, tableContent=
任务剖面 结温误差$/\%$
修正前 修正后
开通过程 27.16 2.50
稳态导通 20.62 0.99
关断过程 12.56 1.73
过载故障保护 15.66 2.17
过压故障保护 13.04 2.08
欠压故障保护 13.75 2.66
短路故障保护 20.85 3.81
), ArticleFig(id=1154041040815251664, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1154040963430342953, language=CN, label=表3, caption=SSPC 热模型参数修正前后结温误差对比, figureFileSmall=null, figureFileBig=null, tableContent=
任务剖面 结温误差$/\%$
修正前 修正后
开通过程 27.16 2.50
稳态导通 20.62 0.99
关断过程 12.56 1.73
过载故障保护 15.66 2.17
过压故障保护 13.04 2.08
欠压故障保护 13.75 2.66
短路故障保护 20.85 3.81
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考虑老化影响的SSPC 功率管热模型自适应在线修正方法
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钱叶彤 , 王莉 , 赵瑞博
电源学报 | 功率半导体器件 2024,22(1): 171-178
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电源学报 | 功率半导体器件 2024, 22(1): 171-178
考虑老化影响的SSPC 功率管热模型自适应在线修正方法
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钱叶彤 , 王莉 , 赵瑞博
作者信息
  • 南京航空航天大学 多电飞机电气系统工信部重点实验室 南京 211000
  • 钱叶彤(1997-),女,硕士研究生。研究方向:固态功率控制器的可靠性及热管理。E-mail:qianyt@nuaa.edu.cn。

    王莉(1969-),女,通信作者,博士。研究方向:飞行器电源系统分析设计、固态配电技术、高频电力电子、故障诊断。E-mail: liwnag@nuaa.edu.cn。

    赵瑞博(1994-),男,硕士研究生。研究方向:固态配电技术。E-mail: zrb@nuaa.edu.cn。

Adaptive Online Update Method for Thermal Model of SSPC Power Device Considering Aging Effects
Yetong QIAN , Li WANG , Ruibo ZHAO
Affiliations
  • Key Laboratory of the Ministry of Industry and Information Technology of the Multi-Electric Aircraft Electrical System Nanjing University of Aeronautics and Astronautics Nanjing 211000 China
出版时间: 2024-01-30 doi: 10.13234/j.issn.2095-2805.2024.1.171
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固态功率控制器 SSPC(solid-state power controller)中功率管的结温监测对SSPC的可靠性有至关重要的作用,热模型法因其无需直接接触测量且方法简单而被广泛使用。然而,功率芯片的老化会导致热路径的退化,器件的结壳热阻抗增加,使实际结温远远超过热网络模型的估计值,导致对器件健康状态的乐观估计。焊料层疲劳失效被认为是SSPC 功率管老化失效的主要原因之一。因此,在 SSPC的寿命周期中实时监测器件的老化状态,并对功率管的热模型进行自适应在线修正,通过测量不受焊料层退化影响的热敏参数来计算热阻作为更新依据,将热阻信息关联焊料层老化状态来更新热模型。所提方法可在不影响 SSPC 正常工作的前提下,实时修正热模型,实验结果验证了方法的有效性。

热模型修正  /  固态功率控制器  /  结温  /  MOSFET  /  老化

The junction temperature monitoring of power devices in a solid-state power controller(SSPC) plays a vital role in the SSPC reliability. The thermal model method is widely used owing to its contactless measurement and simplicity. However, the aging of the power chip will lead to the degradation of the thermal path, and the junction-to-case thermal resistance of the device will increase. As a result, the actual junction temperature may far exceed the value estimated by the thermal network model, leading to an optimistic estimation of the device's state-of-health. The failure of the solder layer is considered to be one of the main reasons for the aging failure of SSPC power devices. In this paper, the device's aging state is monitored in real time during the life of SSPC, and the thermal model of the power device is adaptively updated online. The thermal impedance taken as an update basis is calculated by measuring the temperature-sensitive electrical parameters which are not affected by the degradation of the solder layer, and the thermal impedance information is associated with the aging state of the solder layer to update the thermal model. Using the proposed method, the thermal model can be updated in real time without affecting the normal operation of SSPC, and experimental results verified the effectiveness of this method.

Thermal model update  /  solid-state power controller(SSPC)  /  junction temperature  /  MOSFET  /  aging
钱叶彤, 王莉, 赵瑞博. 考虑老化影响的SSPC 功率管热模型自适应在线修正方法. 电源学报, 2024 , 22 (1) : 171 -178 . DOI: 10.13234/j.issn.2095-2805.2024.1.171
Yetong QIAN, Li WANG, Ruibo ZHAO. Adaptive Online Update Method for Thermal Model of SSPC Power Device Considering Aging Effects[J]. Journal of Power Supply, 2024 , 22 (1) : 171 -178 . DOI: 10.13234/j.issn.2095-2805.2024.1.171
随着多电/全电飞机的发展,先进飞机配电系统逐步取代传统机电式配电系统,固态功率控制器 SSPC (solid-state power controller) 作为先进飞机配电系统的核心部件, 兼具开关、短路保护、过欠压保护、过载保护的功能,其可靠性很大程度上影响了整个飞机配电系统的安全可靠性。
工业界针对已损坏电力电子部件的问卷调查表明,在各类部件中,功率器件的损坏几率最高,占${31}\%{}^{\left\lbrack 1\right\rbrack }$。因此在 SSPC 应用中应更加关注功率器件的可靠性。功率器件失效的因素分为两类:一类是封装失效,另一类是芯片失效。封装失效主要原因是结温过高导致的键合线脱落, 或是长期热循环导致的焊料层疲劳。芯片失效主要分为热击穿和电击穿, 而电击穿的本质最终也是由于温度过高而导致的热击穿。这些失效因素均与最高结温、结温波动和平均结温等因素有关[2-3]。美国空军航空电子整体研究项目表明, 功率 MOSFET 的主要失效原因中, 与温度有关的因素占${55}{\%}^{\left\lbrack 4\right\rbrack }$。因此,有必要对 SSPC 中的关键器件功率管进行实时结温监测。
目前, 国内外常用的功率器件结温测量的方法有 4 种:物理接触法、光学法、热网络法和热敏参数 TSEP(temperature-sensitive electrical parameter)法。 其中光学法和物理接触法需要打开器件封装, 不利于结温的实时监测[5-6]。目前,常用于在线获取结温的方法是热网络法和热敏参数法。
对于 SSPC 而言, 其中功率管存在多种工作模式。在 SSPC 导通、短路、限流、过载和“慢通断”等工作模式下, 功率管的工作区域不同, 例如: 稳态导通时功率管工作在可变电阻区, 限流及开关过程通过控制栅极电压使功率管工作在饱和区[7]。而热敏参数法仅适用于单一任务剖面下的结温测量,相比之下, 热网络模型法可以更好地兼顾 SSPC 各个任务剖面的结温监测。建立热网络模型的要点在于建立准确的实时损耗模型和实时热阻抗模型[89]。然而,功率器件各层材料的热膨胀系数不同, 在器件内部发生重复的热循环时,焊料层将产生裂纹、空隙甚至分层。 这将会导致热路径逐渐退化, 器件的结壳热阻抗增加, 使结温被低估, 结芯的实际结温可能远远超过热网络模型的估计值, 导致对 MOSFET 健康状态的乐观估计,不利于 SSPC 的安全可靠运行。因此,在功率器件的寿命过程中对热模型进行自适应修正以消除焊料层老化对结温监测的影响至关重要。
目前针对老化的热模型修正方法都不能有效应用于 SSPC 的在线修正中。文献[10-11]建立了 IGBT 模块焊料层裂纹与外壳温度分布不均匀程度的直接关系, 通过检测壳温不均匀度来更新热模型, 这种方法只能在对象处于单一任务剖面如模块的功率损耗恒定下适用, 而 SSPC 在工作过程中任务剖面多样, 且壳温的测量精度易受传感器安装位置的影响,不适用于小封装,如 TO-247 封装的 MOSFET 器件。文献[12-13]采用数据驱动的自适应方法, 利用热阻信息关联热路径退化过程来更新模型参数, 但是校正过程需要停机离线进行, 均不适用于 SSPC 功率管的热模型在线修正。
因此, 本文提出一种 SSPC 功率管热模型的在线修正方法, 在不影响 SSPC 正常工作的前提下, 考虑 SSPC 多任务剖面的工作特性, 在 SSPC 的全寿命周期内实时监测焊料层的老化状态, 采用自适应修正方法实时在线更新功率管的热模型参数, 提高结温估计的实时性和准确度, 为 SSPC 的安全可靠运行提供保障。
由于器件各层材料的热失配, 当功率器件内发生重复的热循环时, 焊料层将产生裂纹、空隙甚至分层, 这会导致器件的结壳热阻抗增加, 结芯的实际结温可能远远超过热网络模型的估计值, 不利于 SSPC 的安全可靠运行。因此,需要在 SSPC 的运行过程中对功率管 MOSFET 的热模型进行实时修正。 首先需要实时监测 MOSFET 焊料层的状态, 在发生老化时及时修正热模型的参数。
功率器件的结壳热阻通常作为表征焊料层老化状态的特征量。MOSFET 的结壳稳态热阻${R}_{\mathrm{{th}}\left(\mathrm{{jc}}\right)}$ 的表达式[14]为
${R}_{\mathrm{{th}}\left(\mathrm{{jc}}\right)} =\frac{{T}_{\mathrm{j}}- {T}_{\mathrm{c}}}{P}$
式中:${T}_{\mathrm{j}}$ 为结温;${T}_{\mathrm{c}}$ 为壳温;$P$ 为功率损耗。
用稳态时 MOSFET 结壳的温差比功率损耗$P$ 即可得到稳态结壳热阻${R}_{\mathrm{{th}}\left(\mathrm{{jc}}\right)}$。其中${T}_{\mathrm{c}}$ 可以通过将传感器紧贴器件外壳测量得到,$P$ 通过测量流过功率管的电流${I}_{\mathrm{d}}$ 和 MOSFET 的导通压降${V}_{\mathrm{{ds}}\left(\mathrm{{on}}\right)}$ 得到。 测量稳态热阻的关键在于如何获取功率管稳态导通时的结温${T}_{\mathrm{j}}$。直接接触测量需要打开 MOSFET 封装,测量困难且会改变 MOSFET 的散热路径,因此本文考虑采用热敏参数法来获取结温, 这种间接测量方法不需要打开器件封装,且方便在线获取, 实时计算热阻。由于焊料位于硅区和基板之间的过渡层中, 焊料层内的空洞生长不会影响硅区的物理特性[15],随着焊料层空洞比例的增加,电参数不会表现出明显的退化趋势。文献[16]采用剪断键合线的方式来模拟键合线失效,研究结果表明热敏参数与结温的关系曲线不会因为键合线的断裂而发生变化。 因此本文在 SSPC 的寿命周期内利用 TSEP 间接测量稳态热阻作为实时监测焊料层老化的依据。
TSEPs 主要包含饱和电流、阈值电压、导通电阻或导通压降和开关时间, 但这些参数方法很少应用于 MOSFET。饱和电流法需要在恒定的漏源电压下测量电流[17],实际 SSPC 工作过程中很难保证漏源电压恒定; 阈值电压法通过测量器件的阈值电压, 线性度良好, 但易受噪音干扰, 且需同时监测阈值电压与负载电流,测量复杂[18];开关时间法可在每个开关周期内对器件结温进行非入侵实时监测[19-20],但 SSPC 多采用缓开关控制策略,主动控制功率器件的开通/关断时间;相比之下,导通电阻是一个可用的 TSEP, SSPC 长时间处于稳态导通的任务剖面, 测量导通电阻不会影响 SSPC 的正常运行[21]
接下来需要标定不同结温${T}_{\mathrm{j}}$ 与导通电阻${R}_{\mathrm{{ds}}\left(\mathrm{{on}}\right)}$ 的关系曲线。由于$\mathrm{{SiC}}$ 材料的 MOSFET 具有通流能力强的优势, SSPC 常选用 SiC MOSFET 作为主功率管。本文以型号 C2M0025120D 的 SiC MOSFET 为例,当通入电流${I}_{\mathrm{d}}$$\left({{I}_{\mathrm{d}}< {10}\mathrm{\;A}}\right)$ 时, MOSFET 的功率损耗较低。例如: 当${I}_{\mathrm{d}}= 5\mathrm{\;A}$ 时,稳态导通电阻约为${25}\mathrm{\;m}\Omega$,稳态热阻为${0.24}{}^{\circ }\mathrm{C}/\mathrm{W}$,则结芯温度与壳温之差约${0.15}^{\circ }\mathrm{C}\left({5\mathrm{\;A}\times 5\mathrm{\;A}\times {25}\mathrm{\;m}\Omega \times {0.24}^{\circ }\mathrm{C}/\mathrm{W}= {0.15}^{\circ }\mathrm{C}}\right)$, 此时可以认为芯片不发自热,被测器件稳态导通时的壳温${T}_{\mathrm{c}}$ 可以近似等于结温${T}_{\mathrm{j}}$。当 MOSFET 长时通入较大电流$\left({{I}_{\mathrm{d}}> {10}\mathrm{\;A}}\right)$ 时,功率损耗较大,则芯片自热不可以忽略, 此时可将大电流以脉冲形式通入, 但当大电流持续时间足够短时, 可以认为芯片不发自热。例如:${I}_{\mathrm{d}}= {60}\mathrm{\;A}$,持续时间$t ={100\mu }\mathrm{s}$,瞬态热阻为 0.0026 °C/W,则结芯温度与壳温差约${0.23}^{\circ }\mathrm{C}$ (60 A$\times$ ${60}\mathrm{\;A}\times {25}\mathrm{\;m}\Omega \times {0.0026}\mathrm{{}^{\circ }C}/\mathrm{W}= {0.23}\mathrm{{}^{\circ }C}$ ),可以忽略。
图1 为标定结温${T}_{\mathrm{j}}$${R}_{\mathrm{{ds}}\left(\mathrm{{on}}\right)}$ 关系的测量电路, 其中漏源电压检测电路连接到被测 MOSFET 的漏极和源极,被测器件的导通电流${I}_{\mathrm{d}}$ 和壳温${T}_{\mathrm{c}}$ 分别由检测电阻${R}_{\text{sense }}$ 和热敏电阻${R}_{\mathrm{c}}$ 测量得到。以${I}_{\mathrm{d}}$${60}\mathrm{\;A}$ 为例,标定步骤如下。
步骤 1 将功率管置于恒温箱中, 稳态后认为壳温与结温一致;
步骤 2 使被测器件处于稳态导通状态, 长时通入$5\mathrm{\;A}$ 电流,此时认为器件不发自热,壳温${T}_{\mathrm{c}}$ 可以近似等于结温${T}_{\mathrm{j}}$;
步骤 3 当壳温${T}_{\mathrm{c}}$ 进入稳态时$(3\mathrm{\;{min}}$ 内变化温度小于${0.1}^{\circ }\mathrm{C}$,认为进入稳态),改变负载,使电流迅速切换至${60}\mathrm{\;A}$,持续时间为${100\mu }\mathrm{s}$,壳温和结温可以近似相等,记录此时的${V}_{\mathrm{{ds}}}$${I}_{\mathrm{d}}$,得到当前结温下的${R}_{\mathrm{{ds}}\left(\mathrm{{on}}\right)}$;
步骤 4 改变恒温箱温度, 重复步骤 3, 测温范围 25~150 °C。得到的结温与导通电阻的关系曲线如图2 所示,结温${T}_{\mathrm{j}}$ 与导通电阻${R}_{\mathrm{{ds}}\left(\mathrm{{on}}\right)}$ 的关系可被拟合为
${T}_{\mathrm{j}}= -{142300}{R}_{\mathrm{{ds}}\left(\mathrm{{on}}\right)}^{2}+ {15650}{R}_{\mathrm{{ds}}\left(\mathrm{{on}}\right)} -{287.3}$
因此, 在 SSPC 的运行过程中, 实时测量主功率管$\;\mathrm{{SiC}}$ MOSFET 的导通电阻${R}_{\mathrm{{ds}}\left(\mathrm{{on}}\right)}$,即可通过式 (2) 查表得到 SiC MOSFET 的结温。
热参数的实时更新对于焊料层老化过程中结温估计的准确性至关重要,最常见的热模型可分为 2 种: Cauer 模型和 Foster 模型。Cauer 模型是基于功率管各层材料的特性和结构构建的, 因此若要更新模型参数, 必须精确计算由于焊料层老化引起的材料特性和封装结构的变化。Foster 模型是由实测或模拟瞬态热阻抗${Z}_{\mathrm{{th}}}\left( t\right)$ 曲线拟合的等效模型,由一系列具有解耦时间常数的 RC 单元组成, 模型参数的更新是基于 MOSFET 的线性热行为。与 Cauer 模型相比, Foster 模型更常用于结温估算, 因此本文重点关注 Foster 模型的结温实时更新方法。
建立如图3 所示的三阶 Foster 热网络模型, 瞬态热阻${Z}_{\mathrm{{th}}}\left( t\right)$ 表达式为
${Z}_{\mathrm{{th}}}\left( t\right)= \mathop{\sum }\limits_{{i = 1}}^{n}{R}_{i}\left\lbrack {1 -\exp \left({-\frac{t}{{R}_{i}{C}_{i}}}\right)}\right\rbrack $
${R}_{i}= {\int }_{0}^{{d}_{i}}\frac{1}{{k}_{i}{A}_{i}\left( z\right)}\mathrm{d}z $
${C}_{i}= {\int }_{0}^{{d}_{i}}{\rho }_{i}{c}_{i}{l}_{i}\left( z\right){A}_{i}\left( z\right)\mathrm{d}z $
式中:${R}_{i}$${C}_{i}$ 分别为 Foster 热网络单元中的热阻和热容[12] 分别为第$i$ 层材料的厚度、热导率、比热容、密度;$z$ 为变量,代表该点到该层上表面的距离;${l}_{i}\left( z\right)$${A}_{i}\left( z\right)$ 分别为距离$z$ 处的长度和水平横截面积。
当功率器件发生老化时, 焊料层产生裂缝和空洞, 甚至导致分层, 因此焊料层和裂缝的建模是器件热模型中重要的组成部分, 以反映其不均匀的结构。焊料层和空隙的材料性质如表1 所示。将表1 的参数代入式(4)和式(5)中可以得出, 理论上在相同尺寸下, 空洞的热阻是焊料的 32 倍, 而其热容变化仅为 9%,焊料层老化对热阻的影响比对热容的影响大得多,热容对空洞生长的敏感性较低[12-13]
因此, 本文忽略焊料层老化过程中热容的变化, 重点研究各阶热阻的变化。Foster 热模型参数是从瞬态热阻抗${Z}_{\mathrm{{th}}}\left( t\right)$ 曲线中提取出来的,一般来说, 焊料层老化产生裂缝会缩小焊料层中的热传导区域, 从而使热阻增加, 这就是热模型估算产生误差的重要原因。焊料层的老化会影响 Foster 模型的每一阶热阻的大小, 因此本文忽略老化对热容的影响, 将热阻与老化关联, 对每阶热阻修正为
${R}_{i\left(\text{ aged }\right)} ={R}_{i}\left({1 +\frac{{T}_{\mathrm{j}\left(\text{ measured }\right)} -{T}_{\mathrm{j}\left(\text{ estimated }\right)}}{P{R}_{\text{total }}}}\right)$
式中:${R}_{i}$ 为没有老化效应的第$i$ 层的热阻;${R}_{i\left(\text{aged }\right)}$ 为退化热路径中更新的热阻;${T}_{\mathrm{j}\left(\text{measured }\right)}$ 为热敏参数法测量的结温;${T}_{\mathrm{j}\left(\text{estimated }\right)}$ 为热模型法估计的结温;${R}_{\text{total }}$ 为没有老化效应的热阻之和。式(6)用导通电阻测量的稳态热阻来修正 Foster 模型的各层热阻,以弥补老化效应带来的影响。
本文所提方法的流程如图4 所示。方法的实现包括 3 个功能模块:数据采集计算模块、老化状态监测模块和热模型更新模块。其中,数据采集计算模块在系统运行过程中实时采集系统的漏源电压${V}_{\mathrm{{ds}}}$ 、漏极电流${I}_{\mathrm{d}}$ 、壳温${T}_{\mathrm{c}}$ 、器件的导通电阻${R}_{\mathrm{{ds}}\left(\mathrm{{on}}\right)}$ 、由 1.1 节所述的 TSEP 法查表得到的结温${T}_{\mathrm{j}\left(\text{measured }\right)}$ 、热网络模型实时估计的结温${T}_{\mathrm{j}\left(\text{estimated }\right)}$; 老化状态监测模块实时计算稳态热阻变化值$\Delta {R}_{\mathrm{{th}}}$,即${T}_{\mathrm{j}\left(\text{measured }\right)}$${T}_{\mathrm{j}\left(\text{estimated }\right)}$ 的差值与功率$P$ 的比值; 本文提出的热模型参数自适应方法是一种事件驱动的方法, 仅当$\Delta {R}_{\mathrm{{th}}}> M$ 时,认为 MOSFET 的老化达到一定阈值, 触发事件, 进行热模型参数更新, 否则重新进行数据采集计算。本文设置$M ={0.012}$,象征热阻退化约 5%, 此时需要对热模型参数进行修正。热模型更新模块根据式 (6) 更新热模型的热阻参数, 并将更新后的热阻作为下一次循环的初始值。
直流 SSPC 功率管的热模型在线修正运行流程如图5 所示。自适应更新在直流 SSPC 的稳态导通过程中运行, 可在不影响直流 SSPC 正常运行的前提下更新热模型参数。首先判断直流 SSPC 是否进入稳态导通任务剖面。若直流 SSPC 处于稳态导通阶段,则利用${T}_{\mathrm{j}\left(\text{measured }\right)}$${T}_{\mathrm{j}\left(\text{estimated }\right)}$ 计算稳态热阻的变化值$\Delta {R}_{\mathrm{{th}}}$; 若差值$\Delta {R}_{\mathrm{{th}}}$ 大于所设定的阈值,则认为器件发生一定老化, 热模型参数偏移较大, 需要修正。此时更新 Foster 网络的热阻参数, 完成一次热模型参数的自适应更新。
为了结合 SSPC 的工作特性, 验证所提出方法的有效性,本文采用功率循环加速老化实验[22] 模拟直流 SSPC 的老化过程。在直流 SSPC 中, 正常开通关断的时间以及故障保护的延时时间在设计初期已经固定,系统的额定电流大小也是固定的, 这二者在直流 SSPC 的运行过程中都不会发生改变。为了更加贴合直流 SSPC 的实际运行情况, 本文采用恒定导通关断时间和恒定电流相结合的老化控制策略。
图6 给出了本文设计的 SSPC 功率循环加速老化电路示意, 来模拟 SSPC 中功率管的老化, 其中栅极电压恒定,使功率管保持导通状态。${t}_{1}$ 时刻,开关$\mathrm{S}$ 闭合,回路电流为大电流${I}_{\mathrm{h}}$,用于给器件加热,结温升高,直至达到热平衡状态;${t}_{2}$ 时刻,开关$\mathrm{S}$ 断开,回路电流迅速切换至小电流${I}_{\mathrm{m}}$,目的是使功率管被打开又不发自热,这一阶段器件停止加热,使用强制风冷的方式使功率管结温迅速下降,控制策略如图7 所示。
本文设置小电流${I}_{\mathrm{m}}$$5\mathrm{\;A}$,大电流${I}_{\mathrm{h}}$${60}\mathrm{\;A}$。 每个循环的加热时间为${10}\mathrm{\;s}$,降温时间为${20}\mathrm{\;s}$,整个循环持续时间为${30}\mathrm{\;s}$,结温摆动幅度$\Delta {T}_{\mathrm{j}}$ 约为${80}^{\circ }\mathrm{C}$。漏源电压检测电路被并联在待测 MOSFET 的两端用于测量功率管的漏源电压${V}_{\mathrm{{ds}}}$,回路中串联检测电阻${R}_{\text{sense }}$,通过测量检测电阻上的压降来测量 MOSFET 的漏极电流${I}_{\mathrm{d}}$,热敏电阻${R}_{\mathrm{c}}$ 用于测量 MOSFET 的壳温${T}_{\mathrm{c}}$
本文在直流 SSPC 的寿命过程中, 以 MOSFET 稳态热阻退化 20%的时刻为例, 来验证所提出的热模型在线修正方法的有效性。图8 给出了寿命初期及稳态热阻退化${20}\%$ 时功率管瞬态热阻${Z}_{\mathrm{{th}}}\left( t\right)$ 曲线的对比。在稳态热阻退化 20%后, 在直流 SSPC 稳态导通时通入${60}\mathrm{\;A}$ 电流后, MOSFET 的结温上升,图9 给出了未更新热模型的测量结温${T}_{\mathrm{j}\left(\text{measured}\right)}$ 和估计结温${T}_{\mathrm{j}\left(\text{estimated }\right)}$ 的比较,其中测量结温${T}_{\mathrm{j}\left(\text{measured }\right)}$ 是基于${R}_{\mathrm{{ds}}\left(\mathrm{{on}}\right)}$ 的测量,估计结温${T}_{\mathrm{j}\left(\text{estimated }\right)}$ 是基于 Foster 热模型的实时估计。通过对比可知, 未更新参数的热模型的结温估计与实际测量值的误差高达${5}^{\circ }\mathrm{C}$, 这大大超过了结温监测所允许的误差。因此, 在器件发生老化后, 传统基于热模型的结温估计方法很难获取精确的结温值。
本文考虑老化效应对散热路径热阻的影响, 应用第 1 节提出的热模型自适应系统,在老化过程中根据式 (6) 实时更新的 Foster 热模型。在老化实验测试过程中, 系统每测试到稳态热阻的偏差超过 5%, 进行一次热模型更新。更新后热模型的测量结温和估计结温对比如图10 所示, 更新后热模型的结温估计值与结温测量值的误差小于$1{}^{\circ }\mathrm{C}$,结温监测的精度大大提高。更新前后 Foster 热模型的热阻参数如表2 所示。
更新前的热模型结温估计值和测量值之间测温差为${5}^{\circ }\mathrm{C}$,热阻变化占原始值的${20}\%$,因此将热阻${R}_{1}\text{、}{R}_{2}\text{、}{R}_{3}$ 相应地更新。图10 给出了更新热模型后的测量结温${T}_{\mathrm{j}\left(\text{measured }\right)}$ 和估计结温${T}_{\mathrm{j}\left(\text{estimated }\right)}$ 的比较, 可以看出,结温的误差降低至 1 ℃ 以内,满足结温监测的精度要求, 证明了本文提出的热模型自适应方法的有效性。
将热模型自适应在线修正方法应用于 SSPC 的全寿命周期结温监测中,表3 给出了 SSPC 功率管老化 20%后,热模型参数修正前后的结温误差对比。由表3 可知, 若 SSPC 发生老化后不对热模型参数进行处理, 则各个任务剖面的结温在线监测会产生较大的误差,其中开通过程的结温测量误差最大, 达到 27.16%, 采用本文提出的自适应修正方法对热模型参数进行更新后, SSPC 各个任务剖面的结温误差可缩小至 4%以内,可满足 SSPC 结温在线监测的精度要求。
本文考虑了 SSPC 多任务剖面的工作特性, 在 SSPC 全工作周期内实时监测功率管 MOSFET 焊料层的老化状态, 采用自适应热模型修正方法实时更新热模型的参数。
选取导通电阻${R}_{\mathrm{{ds}}\left(\mathrm{{on}}\right)}$ 作为 TSEP,可在不影响 SSPC 正常运行的前提下间接获取结温, 用于计算稳态热阻来实时监测焊料层的退化状态, 以稳态热阻退化 5%作为热模型的修正依据。本文建立了热模型的老化监测和自适应在线修正系统,将热阻信息关联焊料层老化状态, 实时更新 Foster 热模型参数。本文通过功率循环加速老化实验模拟 SSPC 的全寿命周期,在 SSPC 功率管的热阻老化 20%时, 实验验证了热模型修正方法的有效性, SSPC 全任务剖面下的结温估计精度均有很大提升。本文建立的热模型自适应修正系统可以在不影响 SSPC 正常工作前提下, 实时修正热模型参数, 提高结温监测的实时性和准确度, 为 SSPC 的安全可靠运行提供保障。
  • 国家自然科学基金资助项目(51777092)
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2024年第22卷第1期
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doi: 10.13234/j.issn.2095-2805.2024.1.171
  • 接收时间:2021-02-09
  • 首发时间:2025-07-21
  • 出版时间:2024-01-30
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  • 收稿日期:2021-02-09
  • 修回日期:2021-02-16
  • 录用日期:2021-07-06
基金
National Natural Science Foundation of China(51777092)
国家自然科学基金资助项目(51777092)
作者信息
    南京航空航天大学 多电飞机电气系统工信部重点实验室 南京 211000
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