Article(id=1157001750193459478, tenantId=1146029695717560320, journalId=1146120084050784272, issueId=1157001742186533107, articleNumber=null, orderNo=null, doi=10.19562/j.chinasae.qcgc.2024.08.019, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1707235200000, receivedDateStr=2024-02-07, revisedDate=1711641600000, revisedDateStr=2024-03-29, acceptedDate=null, acceptedDateStr=null, onlineDate=1753780313298, onlineDateStr=2025-07-29, pubDate=1724515200000, pubDateStr=2024-08-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753780313298, onlineIssueDateStr=2025-07-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753780313298, creator=13701087609, updateTime=1753780313298, updator=13701087609, issue=Issue{id=1157001742186533107, tenantId=1146029695717560320, journalId=1146120084050784272, year='2024', volume='46', issue='8', pageStart='1335', pageEnd='1536', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=0, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1753780311389, creator=13701087609, updateTime=1756792467091, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1169635638933467651, tenantId=1146029695717560320, journalId=1146120084050784272, issueId=1157001742186533107, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1169635638933467652, tenantId=1146029695717560320, journalId=1146120084050784272, issueId=1157001742186533107, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1529, endPage=1536, ext={EN=ArticleExt(id=1157001752022176031, articleId=1157001750193459478, tenantId=1146029695717560320, journalId=1146120084050784272, language=EN, title=Analysis and Verification of Fatigue Performance of Vehicle Closures, columnId=null, journalTitle=Automotive Engineering, columnName=null, runingTitle=null, highlight=null, articleAbstract=

A study is conducted on the fatigue failure problem caused by the opening and closing of a car door. Firstly, the transient impact load under the door closing condition is discretized, and the vibration acceleration response signal and frequency response function are collected through the whole vehicle and bench tests respectively. Thus, the transfer path analysis (TPA) method is used to calculate the discretized transient impact load. Secondly, the obtained transient impact load is input into the finite element model of the door, and then the stress-time history response cloud diagram under the door closing condition is obtained, and the fatigue life under the door opening and closing condition is further calculated based on the fatigue damage theory. Finally, the fatigue analysis results based on load identification, the fatigue analysis results based on explicit dynamics and the fatigue test results under the door closed condition are compared and verified with each other. The conclusion shows that the three results are consistent, which has verified the rationality of the method.

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对某汽车车门关闭过程中产生的疲劳失效问题进行了研究。首先,对车门关闭工况下的瞬态冲击载荷进行离散化处理,通过整车和台架实验分别采集振动加速度响应信号和频率响应函数,从而利用传递路径分析(transfer path analysis, TPA)方法计算得到离散化瞬态冲击载荷。其次,将求取的瞬态冲击载荷输入至车门有限元模型中,进而获得关门工况下的应力-时间历程响应云图,进一步由疲劳损伤理论计算车门关闭工况下的疲劳寿命。最后,将基于载荷识别的疲劳分析结果、基于显式动力学的疲劳分析结果以及车门关闭工况下的疲劳实验结果进行对比验证,结论表明三者结果一致性较好,验证了该方法的合理性。

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高大威,教授,博士,E-mail:
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材料 弹性模量/MPa UTS/MPa
DC01 210 000 220
DC04 210 000 240
DC06 210 000 269
ST52 210 000 490
Q235 210 000 431
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材料 弹性模量/MPa UTS/MPa
DC01 210 000 220
DC04 210 000 240
DC06 210 000 269
ST52 210 000 490
Q235 210 000 431
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车辆开闭件疲劳性能分析与验证
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刘哲 1 , 李辉 1 , 高大威 1 , 高云凯 2
汽车工程 | 2024,46(8): 1529-1536
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汽车工程 | 2024, 46(8): 1529-1536
车辆开闭件疲劳性能分析与验证
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刘哲1, 李辉1, 高大威1 , 高云凯2
作者信息
  • 1. 上海理工大学机械工程学院,上海 200093
  • 2. 同济大学汽车学院,上海 201804

通讯作者:

高大威,教授,博士,E-mail:
Analysis and Verification of Fatigue Performance of Vehicle Closures
Zhe Liu1, Hui Li1, Dawei Gao1 , Yunkai Gao2
Affiliations
  • 1. School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai  200093
  • 2. School of Automotive Studies,Tongji University,Shanghai  201804
出版时间: 2024-08-25 doi: 10.19562/j.chinasae.qcgc.2024.08.019
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对某汽车车门关闭过程中产生的疲劳失效问题进行了研究。首先,对车门关闭工况下的瞬态冲击载荷进行离散化处理,通过整车和台架实验分别采集振动加速度响应信号和频率响应函数,从而利用传递路径分析(transfer path analysis, TPA)方法计算得到离散化瞬态冲击载荷。其次,将求取的瞬态冲击载荷输入至车门有限元模型中,进而获得关门工况下的应力-时间历程响应云图,进一步由疲劳损伤理论计算车门关闭工况下的疲劳寿命。最后,将基于载荷识别的疲劳分析结果、基于显式动力学的疲劳分析结果以及车门关闭工况下的疲劳实验结果进行对比验证,结论表明三者结果一致性较好,验证了该方法的合理性。

车门  /  瞬态响应  /  疲劳耐久  /  有限元法

A study is conducted on the fatigue failure problem caused by the opening and closing of a car door. Firstly, the transient impact load under the door closing condition is discretized, and the vibration acceleration response signal and frequency response function are collected through the whole vehicle and bench tests respectively. Thus, the transfer path analysis (TPA) method is used to calculate the discretized transient impact load. Secondly, the obtained transient impact load is input into the finite element model of the door, and then the stress-time history response cloud diagram under the door closing condition is obtained, and the fatigue life under the door opening and closing condition is further calculated based on the fatigue damage theory. Finally, the fatigue analysis results based on load identification, the fatigue analysis results based on explicit dynamics and the fatigue test results under the door closed condition are compared and verified with each other. The conclusion shows that the three results are consistent, which has verified the rationality of the method.

vehicle door  /  transient response  /  fatigue durability  /  finite element method
刘哲, 李辉, 高大威, 高云凯. 车辆开闭件疲劳性能分析与验证. 汽车工程, 2024 , 46 (8) : 1529 -1536 . DOI: 10.19562/j.chinasae.qcgc.2024.08.019
Zhe Liu, Hui Li, Dawei Gao, Yunkai Gao. Analysis and Verification of Fatigue Performance of Vehicle Closures[J]. Automotive Engineering, 2024 , 46 (8) : 1529 -1536 . DOI: 10.19562/j.chinasae.qcgc.2024.08.019
车门作为全车使用最频繁、最重要的开闭件,其疲劳耐久性能预估已然成为汽车产品开发阶段的关键步骤,直接影响着用户体验以及车辆的整体寿命1。一般情况下车门的耐久性能都通过车门关闭工况下的疲劳实验来评估,显然这种方法成本高昂且耗时,相比之下,计算机仿真分析则可以在开发前期介入,并大幅缩短实验周期与成本2-5
迄今为止,国内外众多学者在车门关闭疲劳方面做了大量的工作。Unadkat等6通过模态叠加法的瞬态分析获得瞬态应力-时间历程,在执行多次设计迭代后使仿真的计算时间和应力收敛更快,最后通过实验验证了其准确性。Shrivastava等7通过车门关闭非线性瞬态仿真联合物理实验的方法,研究主次密封和门闩之间的载荷分布对于车门结构和寿命的影响,结果表明仿真与实验结果一致性较好。秦训鹏等8采用面心复合设计方法构建了车门3阶模态的2阶响应面函数,实现了通过改变车门厚度进行轻量化设计的目标。龙岩等9 分析了多项重要参数对车门疲劳寿命的影响,并利用多目标粒子群算法对车门进行了轻量化和疲劳寿命优化设计。Liu等10结合测试载荷与直接瞬态响应法预测货车车门薄弱位置,结果表明实验与仿真一致性较好。Kapadnis等11结合蒙特卡洛模拟与实验设计方法建立了车门可靠性设计优化流程,实现了预测车门耐久性概率分布的目标,并通过大量有限元模型验证了该流程的准确性。Song等12对车门关闭疲劳耐久分析发现,基于线性应力的方法在较高应力和较短疲劳寿命下更为保守,而基于非线性应力的方法在低周疲劳问题上更为准确。
传递路径分析(transfer path analysis, TPA)方法广泛应用于汽车产品开发阶段。吕来等13提出了时域工况传递路径分析方法,利用简易车身骨架验证了该方法具有较好的精度。刘哲等14通过TPA方法求取离散化载荷并将其输入至有限元模型,建立车门辐射噪声时域边界元模型预测车内噪声,验证了该方法的可行性。毛杰等15使用时域TPA方法分析出某频段路噪主要来源于后副车架安装点位置,再通过尾门的结构优化降低噪声传递函数,进而提高开发效率。唐中华等16提出了整车虚拟TPA的振动噪声诊断方法,并通过修改贡献量较大的传递路径优化了车内的振动噪声指标。徐铁等17提出了一种基于结构动力学修改技术的TPA方法,并采用车架案例分析验证了其理论的正确性。潘公宇等18针对某车怠速抖动问题,通过TPA技术建立悬置系统优化数学模型,进而采用遗传算法获取最优刚度参数,并结合实验结果验证了方法的有效性。
时至今日,研究人员在车门寿命预测方面以及TPA方法在汽车开发中的应用上做了大量研究工作。上述车门疲劳寿命的研究主要分为两类:一类先是通过有限元方法对车门的疲劳寿命进行预估,进而优化车门结构;另一类则是通过对比改进的有限元动态仿真和完整物理实验得到的疲劳结果,从而验证所提出方法的准确性。上述两种研究方法中的有限元部分都是传统的非线性瞬态仿真流程,该流程完全通过有限元方法模拟车门关闭工况,最终获得关门时的瞬态应力-时间历程,在显式动力学分析中考虑网格质量、车门与车身的接触设置等具体因素的影响,有限元模拟中车门所受的载荷与真实工况下仍有差异,该方法显然具有一定的局限性。
本文运用TPA理论进行载荷识别的方法,是利用实验采集车门关闭时参考点的加速度振动响应和激励点至参考点的频率响应函数,反推求得激励点的离散化载荷。将其作为输入量导入有限元模型中进行瞬态分析,再将分析出来的应力历程导入nCode DesignLife中进行疲劳分析。该方法精确求出了关门工况下的瞬态冲击载荷,为有限元疲劳分析提供了实验支撑,并为车门开发设计提供了新思路。
在车门关闭耐久性能分析中,本文结合疲劳分析理论与TPA理论,实现仿真分析与实验测试的有机融合。车门疲劳问题主要涉及钣金件在多次重复关闭冲击载荷作用下,因累计损伤所引起钣金件的裂纹萌生、扩展、直至断裂的过程13。基于车门关闭工况的受力特性,采用载荷识别方法、名义应力S-N疲劳分析方法、Miner线性累计损伤理论进行车门关闭耐久性能分析。TPA理论将目标点响应分解为各个载荷所对应传递路径的贡献量19,通过载荷识别方法得到激励点处瞬态冲击载荷则可以作为载荷谱用于求解车门关闭工况下的应力-时间历程。结合名义应力S-N曲线获得车门单次关闭工况下的损伤值。Miner线性累计损伤理论认为疲劳损伤是线性的、可叠加的20。故通过TPA理论中载荷识别方法进行车门关闭耐久性能分析在理论上是可行的。
本文按如下方法进行车门疲劳分析,具体分析方法如图1所示,具体步骤如下:
(1)在整车实验中采集参考点的加速度振动响应;
(2)在台架实验中采集激励点至参考点的频率响应函数;
(3)通过TPA理论求解激励点的瞬态冲击载荷;
(4)建立车门有限元模型以及简化的白车身有限元模型;
(5)将步骤(3)中求得的瞬态冲击载荷加载到车门有限元模型上进行瞬态分析,同时建立LS-DYNA的非线性瞬态仿真模型,分别求取仿真的应力-时间历程;
(6)将步骤(5)中运用不同方法求得的应力-时间历程导入nCode DesignLife软件中分别进行车门的疲劳计算;
(7)最后将仿真数据与实验结果进行对比,并探讨方法的可行性。
本文所研究的是在玻璃全开状态下,车门关闭速度为1.5 m/s的工况下车门的疲劳寿命,为了利用TPA理论对关门载荷进行计算,需要在车门上设置一定数量的激励点和参考点。车门在关闭瞬时会受到密封条和锁机处的瞬态冲击载荷,为了对密封条处的载荷进行量化计算,需要对其进行离散化处理,离散数量为8个(A1-A8),锁机处的冲击载荷激励点为A9,如图2所示。由TPA理论可知,必须要设置激励点数量两倍或两倍以上的参考点,才能求取激励点载荷,本文设置的参考点所在位置如图3所示。密封条由于其自身材料的非线性性质,其所受的冲击载荷仅为Y方向,而锁机处则是受到XYZ 3个方向上的冲击载荷,故离散化后的激励点自由度易算出,为1×8+3×1=11,参考点的自由度为3×16=48,满足上述参考点的数量设置要求。
整车实验采集加速度振动响应,本文使用LMS公司的型号为LMS SC316‐UTP的120通道的信号采集系统。3项加速度传感器粘贴在图3中参考点所在位置,实验图片如图4所示。
通过弹性绳控制车门关闭的瞬时速度是车门关闭实验以及车门耐久性实验的常用方法。因为弹性绳产生的弹力在弹性范围内与其伸长量成正比,再利用速度传感器与之配合就可以有效地控制车门的关闭速度。本文实验将关门速度统一设置为1.5 m/s。将弹性绳的一端固连在车门内饰板侧,另一端固连在车身内侧,同时在左后车门侧固定有速度传感器检测车门关闭的瞬时速度。
台架实验的目的是获得激励点至参考点的频率响应函数,为此须利用力锤敲击图2所示9个激励点处,在图3所示参考点处粘贴和图4中型号一样的三向加速度传感器,测量参考点处的加速度响应。力锤敲击5次的平均值作为所需的频率响应函数。
基于第3节实验采集到的参考点加速度振动响应和激励点至参考点的频率响应函数,再利用TPA理论公式求出激励点(图2)处的瞬态冲击载荷-时间历程,A1-A8点Y向的激励载荷以及A9点XYZ三向激励载荷(部分)如图5所示。
图5所示激励载荷的时间历程可以发现,在车门关闭过程中,车门所受的瞬态冲击载荷是极短的,约为0.3 s,与关门实际工况相符。然后将瞬态冲击载荷加载到已经建立好的车门有限元模型的激励点处,求解模型在关门时的瞬态应力-时间历程。图6所示为利用上述方法得到的车门在某一时刻的瞬态应力云图,显然在车门上下铰链处以及门锁处存在较大应力,该应力分布符合关门时车门的实际受力情况。
通过给有限元模型加载激励载荷,得到车门关闭瞬时的应力-时间历程,将Optistruct求解得到的H3D和op2文件导入nCode中进行疲劳寿命分析。联合nCode创建疲劳分析模块的分析流程21,如图7所示。在nCode中的SNAnalysis模块中根据本文的需求,设置处理类型为Material,事件处理方式为CombinedFast,应力修正方式为Goodman。由于车门开闭总成材料较多,均用拉伸实验测出S-N曲线过于繁琐,因此在nCode中可以输入材料的极限拉伸强度(UTS),便可自动拟合出材料的S-N曲线,所需部分材料的UTS如表1所示。车门主体部分材料采用DC01、DC04以及DC06,车门铰链部分采用强度较高的ST52,加强板件为Q235。在载荷加载设置中,选用Time step直接调用有限元分析应力-时间历程,进行10万次循环。
nCode疲劳分析结果如图8所示,车门较大损伤出现位置在车门内板左下角焊点附近,该位置损伤值为1.142,已经大于1,发生疲劳破坏。
显式动力学疲劳分析是利用有限元方法对车门关闭瞬时工况进行非线性瞬态疲劳仿真。通过模型缩减,车门开闭模型只须取1/4的白车身与车门配合,rigid刚性单元可以有效传递载荷,车门各钣金件之间采用rigid刚性单元进行连接。车门与白车身通过车门铰链连接,车门铰链以及车门门锁的旋转通过revJoints连接进行模拟。焊点在疲劳分析中尤为重要,采用*MAT_SPOTWELD (MAT_100)材质卡的三维六边形单元对白车身和车门点焊进行模拟。焊缝焊接采用*MAT_SPOTWELD (MAT_100)的MIG_BEAM单元进行模拟,螺栓采用RgdBody单元进行模拟。模型整体采用5 mm的网格,所建车门开闭模型节点数量为398 354个,网格数量为402 872个。LS-DYNA非线性瞬态仿真有限元模型如图9所示。
初始状态下车门呈打开状,选择的车门点集定义其速度为1.5 m/s,同时在车门铰链处设置车门旋转的全局坐标,车门速度加载示意如图10所示。车门开闭模型约束点如图11所示,共1 932个节点,约束其6个方向的自由度。最后施加全局重力,提交到LS-DYNA中进行求解。
在LS-DYNA非线性瞬态碰撞分析中须考虑沙漏能大小,研究表明22沙漏能小于总能量的5%时分析结果才是可靠的,这一点对于验证本文有限元建模的准确性非常重要。由图12可见,本仿真沙漏能明显小于总能量的5%,能量分布与实际相符。其关门瞬间应力分布结果如图13所示,车门上最大应力同样出现在车门上下铰链螺栓孔连接处以及车门门锁附近,这与运用TPA理论进行载荷识别的疲劳分析方法求取的应力在数值和分布上均有较好的一致性。
以车门关闭瞬间A1点(图2)载荷变化为例。在上述基于显式动力学的非线性瞬态仿真结果中,提取A1点Y方向上的载荷-时间历程,与基于TPA理论获得的载荷历程进行对比,结果如图14所示。两者的历程趋势基本相似,波峰和波谷的位置也较为接近,该对比结果表明,基于载荷识别与基于显式动力学的非线性瞬态仿真这两种方法在获取车门关闭瞬时工况下的载荷-时间历程具有较好的一致性。
图15所示为车门内板几何中心点处,通过两种方法分析提取的加速度响应对比,两者在趋势和峰值上的一致性较好,进一步验证了运用载荷识别方法对车门关闭工况进行分析的方法具有较高的准确性。
通过上述关键节点的载荷以及加速度对比可知,两次对比的曲线虽然在趋势和峰值上的一致性较好,但仍然存在一定差异。造成这一现象的原因是基于载荷识别的疲劳分析方法是将离散载荷施加于车门有限元模型之上,而基于显式动力学的疲劳分析方法是车门绕铰链作旋转运动撞击至车身有限元模型,故两者存在一定的误差。
在非线性瞬态分析之后将LS-DYNA求解得到的包含应力-时间历程的d3plot结果文件导入nCode,后续操作流程与4.1节类似,这里不做过多赘述。车门寿命计算结果如图16所示。根据损伤云图所示,车门内板左下角焊点连接处存在明显损伤,大小为1.271,与上节基于载荷识别方法计算得到的疲劳结果无论是在损伤位置还是损伤数值上均基本吻合。由图6图13可见,虽然在上述两种方法下车门上下铰链处都存在较大应力,但该区域采用强度较高的材料且设有加强板件,故该区域没有发生损伤。
最后根据车辆可靠性实验要求,对车门进行10万次关闭实验,发现车门内板左下角焊点处出现明显开裂损伤,车门关闭疲劳实验结果如图17所示。基于载荷识别的疲劳分析和基于显式动力学的疲劳分析结果以及车门关闭工况下的疲劳实验结果三者互为交叉验证,发现在损伤破坏位置上较为吻合,验证了上述方法的可行性。
本文基于TPA理论中载荷识别方法进行疲劳分析,利用台架实验和整车实验,采集车门关闭时的频率响应函数和瞬态加速度振动响应,求出车门关闭时的瞬态离散化载荷,进而将其作为输入量导入有限元模型中进行瞬态分析,再把分析出来的应力-时间历程导入nCode DesignLife中进行疲劳分析。之后通过Hypermesh联合LS-DYNA建立车门关闭工况下的显式动力学疲劳分析模型。将上述两种损伤结果结合实测结果进行对比验证,发现三者结果具有较好的一致性。本文得到的结论如下:
(1)利用TPA理论中载荷识别方法与基于显式动力学方法获取的车门关闭工况下的瞬态冲击载荷时间历程在趋势和峰值上的一致性较好,说明TPA理论中载荷识别方法可用于求取关门工况下的瞬态冲击载荷。
(2)利用两种方法获取的车门内板几何中心点处加速度响应曲线在趋势和峰值上一致性较好,说明利用TPA理论求取的瞬态冲击载荷可用于车门关闭工况仿真分析。
(3)车门疲劳实验与基于载荷识别的疲劳分析得到的疲劳损伤位置均在车门内板左下角处,结果表明本文提出的利用TPA理论中载荷识别方法用于车门关闭耐久性能分析是可行的。
  • 国家自然科学基金(52175239)
  • 安徽省自然科学基金(2308085QE158)
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2024年第46卷第8期
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doi: 10.19562/j.chinasae.qcgc.2024.08.019
  • 接收时间:2024-02-07
  • 首发时间:2025-07-29
  • 出版时间:2024-08-25
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  • 收稿日期:2024-02-07
  • 修回日期:2024-03-29
基金
国家自然科学基金(52175239)
安徽省自然科学基金(2308085QE158)
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    1. 上海理工大学机械工程学院,上海 200093
    2. 同济大学汽车学院,上海 201804

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高大威,教授,博士,E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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