Article(id=1190334494801498205, tenantId=1146029695717560320, journalId=1189645257101713411, issueId=1190334493203468372, articleNumber=null, orderNo=null, doi=10.19822/j.cnki.1671-6329.20240152, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=null, receivedDateStr=null, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1761727458906, onlineDateStr=2025-10-29, pubDate=1749052800000, pubDateStr=2025-06-05, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1761727458906, onlineIssueDateStr=2025-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1761727458906, creator=13701087609, updateTime=1761727458906, updator=13701087609, issue=Issue{id=1190334493203468372, tenantId=1146029695717560320, journalId=1189645257101713411, year='2025', volume='', issue='6', pageStart='1', pageEnd='62', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1761727458525, creator=13701087609, updateTime=1761728912240, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1190340590614184021, tenantId=1146029695717560320, journalId=1189645257101713411, issueId=1190334493203468372, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1190340590618378326, tenantId=1146029695717560320, journalId=1189645257101713411, issueId=1190334493203468372, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=42, endPage=47, ext={EN=ArticleExt(id=1190334494977658974, articleId=1190334494801498205, tenantId=1146029695717560320, journalId=1189645257101713411, language=EN, title=Algorithm Analysis of Opening and Closing Force of Automotive Tailgate Based on PLG System, columnId=1190334493794865238, journalTitle=Automotive Digest, columnName=Special Topic on the Applications of Artificial Intelligence in Intelligent Connected Vehicles, runingTitle=null, highlight=null, articleAbstract=

To optimize the opening and closing forces of the automotive Power Lift Gate (PLG) system, the literature on algorithms related to lift gate forces is reviewed, and a mechanical model of the lift gate system is established. The expressions for the moment exerted by the support rod on the lift gate and the moment exerted by gravity on the lift gate are derived, and the relationships between the length of the support rod, the force arm of the support rod, and the opening angle are analyzed. A simulation model is created using simulation software to perform calculations, and the rationality of the expressions is verified. This study provides a theoretical foundation and optimization direction for the design and improvement of PLG systems.

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为了优化汽车电动尾门(PLG)系统的开闭力,综述了汽车尾门开闭力算法方面的文献,建立了汽车尾门系统力学模型,推导出撑杆对尾门的力矩和重力对尾门的力矩表达式,分析撑杆长度、撑杆力臂与开门角度的关系。通过仿真软件建立模型进行仿真计算,验证了表达式合理性,为PLG系统的设计和改进提供了理论依据和优化方向。

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袁文华,教授,博士,主要研究方向为内燃机节能与排放控制,
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项目 参数
尾门质心X坐标 -414.75
尾门质心Y坐标 0.02
尾门质心Z坐标 549.67
转轴至质心距离( L O G 688.59
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车门质心坐标及转轴至质心距离长度参数表 mm

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项目 参数
尾门质心X坐标 -414.75
尾门质心Y坐标 0.02
尾门质心Z坐标 549.67
转轴至质心距离( L O G 688.59
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参数 数值
门重/ N 267.25
γ/( °) 40.5
L O G / m m 688.59
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M g计算输入参数

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参数 数值
门重/ N 267.25
γ/( °) 40.5
L O G / m m 688.59
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参数 数值
内部阻力 f / N 103.46
最小撑杆长度 L m i n / m m 345
最小弹簧力 F m i n / N 400
OB长度 a / m m 135.4
OA长度 r / m m 477.28
关门时OA与铅垂线的夹角 α /( °) 35.6
关门时OB与铅垂线的夹角 β/( °) 22.1
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Mb计算输入参数

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参数 数值
内部阻力 f / N 103.46
最小撑杆长度 L m i n / m m 345
最小弹簧力 F m i n / N 400
OB长度 a / m m 135.4
OA长度 r / m m 477.28
关门时OA与铅垂线的夹角 α /( °) 35.6
关门时OB与铅垂线的夹角 β/( °) 22.1
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基于PLG系统的汽车尾门开闭力优化分析*
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黄森 1, 2 , 袁文华 1 , 伏军 1 , 马仪 1
汽车文摘 | 人工智能在智能网联汽车中的应用技术专题 2025,(6): 42-47
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汽车文摘 | 人工智能在智能网联汽车中的应用技术专题 2025, (6): 42-47
基于PLG系统的汽车尾门开闭力优化分析*
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黄森1, 2, 袁文华1 , 伏军1, 马仪1
作者信息
  • 1 邵阳学院,邵阳 422000
  • 2 中汽研汽车检验中心(广州)有限公司,广州 511340

通讯作者:

袁文华,教授,博士,主要研究方向为内燃机节能与排放控制,
Algorithm Analysis of Opening and Closing Force of Automotive Tailgate Based on PLG System
Sen Huang1, 2, WenHua Yuan1 , Jun Fu1, Yi Ma1
Affiliations
  • 1 Shaoyang University, Shaoyang 422000
  • 2 CATARC Automotive Test Center (Guangzhou) Co., Ltd., Guangzhou 511340
出版时间: 2025-06-05 doi: 10.19822/j.cnki.1671-6329.20240152
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为了优化汽车电动尾门(PLG)系统的开闭力,综述了汽车尾门开闭力算法方面的文献,建立了汽车尾门系统力学模型,推导出撑杆对尾门的力矩和重力对尾门的力矩表达式,分析撑杆长度、撑杆力臂与开门角度的关系。通过仿真软件建立模型进行仿真计算,验证了表达式合理性,为PLG系统的设计和改进提供了理论依据和优化方向。

PLG系统  /  汽车尾门  /  开闭力优化  /  电动撑杆

To optimize the opening and closing forces of the automotive Power Lift Gate (PLG) system, the literature on algorithms related to lift gate forces is reviewed, and a mechanical model of the lift gate system is established. The expressions for the moment exerted by the support rod on the lift gate and the moment exerted by gravity on the lift gate are derived, and the relationships between the length of the support rod, the force arm of the support rod, and the opening angle are analyzed. A simulation model is created using simulation software to perform calculations, and the rationality of the expressions is verified. This study provides a theoretical foundation and optimization direction for the design and improvement of PLG systems.

PLG system  /  Automotive tailgate  /  Opening and closing forces optimization  /  Electric strut
黄森, 袁文华, 伏军, 马仪. 基于PLG系统的汽车尾门开闭力优化分析*. 汽车文摘, 2025 , (6) : 42 -47 . DOI: 10.19822/j.cnki.1671-6329.20240152
Sen Huang, WenHua Yuan, Jun Fu, Yi Ma. Algorithm Analysis of Opening and Closing Force of Automotive Tailgate Based on PLG System[J]. Automotive Digest, 2025 , (6) : 42 -47 . DOI: 10.19822/j.cnki.1671-6329.20240152
随着汽车工业快速发展,汽车的舒适性和智能性成为各大车企的重点研究方向。传统的汽车尾门系统需要人工操作,不能实现自动闭合,费时费力,而新型电动尾门系统(Power Lift Gate, PLG)操作简单、智能化程度高,不仅可以实现自动闭合,而且配置传感器可以实现“防夹”“防撞”“脚踢操控”等功能,成为消费者关注的焦点[1]。目前,一些学者和研究人员对电动尾门系统进行了分析和研究。国外研究方面,Salunkhe等[2],通过材料创新与轻量化设计,实现对PLG系统进行静态和动态仿真分析,结合CATIA V5建模与物理试验数据验证,为电动尾门驱动组件的优化提供了科学依据,推动了PLG系统轻量化与智能化技术的发展。Siahaan等[3]通过智能控制创新与执行器力学分析,为汽车尾门开闭力优化提供了动态响应与用户体验并重的设计思路。其核心价值在于将传统力学校核(如扭矩计算)与新兴传感技术结合,拓宽了尾门系统优化的维度,为后续研究在环境适应性、长期可靠性及智能化扩展等方面奠定了基础。Dhanvijay等[4]开发了一种基于可编程逻辑控制器(Programmable Logic Controller, PLC)的气动尾门冲击设备控制器,用于尾门部件的结构和功能完整性校核。尽管国外研究在舒适性提升方面取得较多进展,但对PLG系统力学特性的研究仍较为有限。国内研究方面,刘斌[5]分析了PLG系统的控制原理,建立了不同路面坡度下的力学模型,分析了车辆位置状态对尾门受力的影响。刘福强、赵岩[6]研究了气弹簧在不同温度工况下的输出力计算方法,并结合工程实例优化了尾门开启设计。里程旭[7]分析了电动尾门撑杆的手动操作力、悬停功能及噪声性能,列举了电动撑杆支撑力不足、撑杆低温环境异响、撑杆常温或高温环境异响3个电动尾门撑杆典型故障及其解决措施。邹宏[8]以功能安全标准为指导分析电动尾门控制系统的复杂功能和安全技术要求,并采用基于模型设计的开发方法,对电动尾门控制器应用层的控制逻辑进行设计,有效降低了汽车电动尾门发生非预期功能失效的风险。韦康成等[9]以全金属单驱电动尾门开发车型为例,通过建立力学模型,研究不同工况对尾门性能的影响。通过CAE分析和实车试验,验证了尾门强度、间隙面差、变形量等性能优化结果。吴越强等[10]主要研究了电动尾门系统的结构组成、系统功能及电动尾门的应用技术方案,并且针对电动尾门系统的核心部件执行机构的设计与研究。为了解决电动尾门耐久试验工况多、周期长、严重影响项目开发进程的问题,沈奕锋等[11]利用Modbus TCP、TCP/IP、Text API等通信技术实现了对多种试验设备的自动化集成控制,并利用LabVIEW平台,实现了PLG耐久试验的自动化控制与数据监测。
本文通过理论分析和算法推导,建立一套科学合理的开闭力优化方法,旨在优化PLG系统汽车尾门开闭力问题,为PLG系统的设计和改进提供理论依据和优化方向。
本文以SUV汽车的电动撑杆为例进行简化动态力学分析。在力学模型中,尾门本体被视为一个刚体,其运动受到重力、弹簧力、驱动力以及空气阻力等多种力的共同作用。在建立力学模型前,需要对系统相关条件进行假设,并对无关条件进行约束:
(1)假定尾门铰链处在尾门旋转时没有摩擦:忽略铰链处的摩擦力。
(2)假定电动撑杆与车身及尾门的连接处在尾门旋转时无摩擦:忽略连接处的摩擦力。
(3)假设汽车尾门系统沿整车坐标系X-Z平面左右对称:如图1所示(参照GB11562附录B,图B.1中的Y基准平面[12]),基于对称性简化分析过程。
(4)忽略撑杆自身重力:在力学模型中,假设撑杆的质量对系统的影响可以忽略不计。
(5)忽略撑杆内倾角对施力方向的影响:假设撑杆的内倾角对施力方向的影响可以忽略。
(6)忽略其他振动和干扰因素:在分析过程中,忽略由路面振动、风阻或其他外部因素引起的干扰,专注于主要力学特性的研究。
尾门力学模型建立如图2所示。其中,各参数定义如下:αOA与铅垂线的夹角;βOB与铅垂线的夹角;γ为关门时OG与铅垂线的夹角;θ为尾门开启角度;∠AOB=ΦOA=rOB=aAB=cdAB延长线到O点距离。
在忽略撑杆内倾角对施力方向影响的条件下,力学模型可以简化为投影在车辆坐标系的X-Z平面的二维模型。为了探究尾门运动的力学特性,需要围绕尾门开启角(θ角)建立相关表达式。其中,位置动态变化的关键点为撑杆与车身的连接点(A点)以及车门重心(G点)。通过分析这些点的运动关系,可以建立尾门开闭过程中的力学模型,为优化设计提供理论依据。
G x即车门重心点G在运动切线方向的分量, G x随开门角度变化而变化,因此讨论 G x与开门角度的关系,可以推导门重心对尾门力臂随运动变化的关系。 G x与尾门开启角度θ关系分为2种:G低于Gg= G x位置点时,如式(1);G高于Gg= G x位置点时,如式(2)。
$G_{x}=G_{g} \times \cos [90-(\gamma+\theta)]$
$G_{x}=G_{g} \times \cos [(\gamma+\theta)-90]$
式中:γ为关门时OG与铅垂线的夹角,Gg为车门质量,θ为尾门开启角。
从计算结果来看,式(1)和式(2)仅存在正负号差别,正负号仅代表力的方向。由于Gg方向始终垂直地面,因此无论是高于还是低于Gg= G x位置点,G的切向力方向均相同。因此,用式(1)即可表达式(2)的情况,即任意开门角度下的G切向力均可用式(1)表示。
在开关门动作过程中,由于撑杆长度会随尾门开启角度的变化而变化,需要先建立撑杆长度与开门角度的关系。由于尾门开启角度不在∠AOB中,无法直接与AB的长度建立关系式,因此需要对∠AOBθ的关系进行转换。∠AOB的角度Φ与车门运动过程中变量尾门开启角θ关系式为:
$\Phi=\theta+(\alpha-\beta)$
式中:Φ为∠AOB角度,βOB与铅垂线的夹角,αOA与铅垂线的夹角,θ为尾门开启角。
尾门撑杆AB的长度c与∠AOB角度Φ的关系式为:
$c=\sqrt{\left.a^{2}+r^{2}-2 a r \cos \Phi\right)}$
式中:aOB长度,rOA长度,cAB长度。
结合式(3)、式(4)得出尾门撑杆AB的长度c与尾门开启角θ的关系为:
$c=\sqrt{a^{2}+r^{2}-2 a r \cos ([\theta+(\alpha-\beta)]}$
式中:βOB与铅垂线的夹角,αOA与铅垂线的夹角,θ为尾门开启角。
在开门过程中,撑杆力臂也会随尾门开启角度的变化而变化。如图3所示,AB延长线到O点的距离为d,即为撑杆对车门施加力臂的长度。根据ΔAOB的面积计算公式,可得:
$S_{\triangle A O B}=0.5 \times a \times r \times \sin \Phi$
$S_{\triangle A O B}=0.5 \times c \times d$
式中:Φ为∠AOB角度,aOB长度,rOA长度,cAB长度,dAB延长线到O点距离。
结合式(3)、式(6)、式(7),可以得出撑杆对车门施加力臂的长度d与尾门开启角θ的关系式为:
$d=\frac{a \times r \times \sin [\theta+(\alpha-\beta)]}{c}$
式中:dAB延长线到O点距离,βOB与铅垂线的夹角,αOA与铅垂线的夹角,θ为尾门开启角。
汽车PLG系统在整个运动过程主要受撑杆弹簧支撑力Fk、电机力Fe以及尾门自身的重力G影响,如图3所示。其中,撑杆最短长度为Lmin,撑杆最长长度为Lmax。因此,需要分别分析撑杆力F对车门的力矩Mb的关系;以及车门重量 G g对车门力矩Mg的关系。这两个力矩共同对整个尾门开关过程产生的动态力学变化。
撑杆力F由3个力值组成:撑杆内部最大静摩擦力f、撑杆弹簧力Fk和撑杆电机力Fe。其中,最大静摩擦力f为固定值,撑杆电机力Fe是可控制参数。为便于计算,此处将电机力Fe定为某个固定力值。在开关门过程中,撑杆力F直接受弹簧力Fk影响,随着开关门角度θ变化,撑杆弹簧压缩或伸展的变化直接影响撑杆弹簧力Fk,如图4所示。
图4可知,弹簧力Fk的最大值Fmax对应弹簧压缩距离最短的位置Lmin,而弹簧力最小值Fmin对应弹簧压缩距离最长的位置LmaxLmin为解锁开门位置,Lmax为开门最大角度位置。尾门开闭过程中的撑杆行程为:
$\Delta L=L_{\max }-L_{\min } $
根据胡克定律,弹簧系数K可表示为:
$K=\left(F_{\max }-F_{\min }\right) / \Delta L$
尾门开闭过程中的某个角度的撑杆长度为c,则在尾门开闭过程中的弹簧力Fk和任意开启角度的撑杆力的计算公式为:
$F_{\mathrm{k}}=K \times\left(c-L_{\min }\right)+F_{\min }$
$F=\left[F_{\mathrm{e}}-f \pm K \times\left(c-L_{\min }\right)+F_{\min }\right]$
式中: F k为弹簧力, F e为撑杆力, f为内部阻力, K为弹簧系数,cAB长度, L m i n为撑杆最短长度, F m i n为弹簧初始力。
图3所示,撑杆对尾门的力矩Mb的力臂为d,撑杆力为F,任意尾门开启角度下撑杆对尾门的力矩关系式为:
$\begin{aligned} M_{\mathrm{b}}= & {\left[F_{\mathrm{e}}-f \pm K \times\left(c-L_{\min }\right)+F_{\min }\right] \times a \times r \times } \\ & \sin [\theta+(\alpha-\beta)] / c \end{aligned}$
式中: M b为撑杆对尾门的力矩, aOB长度, rOA长度, θ为尾门开启角, αOA与铅垂线的夹角, βOB与铅垂线的夹角。
在开门过程中 G gF方向相反,在关门过程中方向相同,且在任意时刻 G g的方向均与地面垂直,力矩的方向与力臂垂直。因此,需要分析沿O点旋转的车门重心G点的切向力 G x。尾门开闭过程中任意开启角度的Mg为:
$M_{g}=G_{g} \times \cos [90-(\gamma+\theta)] \times L_{O G}$
式中: M g为重力对尾门的力矩, G g为车门重力, L O GO点旋转到车门重心G点的长度, γ为关门时 L O G与铅垂线的夹角, θ为尾门开启角度。
Δ M M g M b的差值,是决定尾门开关动态性能的关键参数。通过优化ΔM,可以提升电动尾门的性能,主要研究方向包括:
(1)悬停功能与随动功能的优化:为了实现电动尾门的悬停功能,ΔM应尽可能大,同时弹簧力Fk的最小值应尽可能小,以优化弹簧设计;为了实现电动尾门的随动功能(即人员操作更轻松),ΔM不应过大。在运动过程中,MgMb的值越接近,操作越轻松。
(2)减少ΔM<0的占比:在整个开关门过程中,当ΔM>0时,撑杆力F较小,有利于节能;开门时,随着开门角度变大,弹簧力Fk线性下降,而撑杆力Fe波动较小且上升趋势平缓,更节能;关门时,随着开门角度变小,弹簧力Fk线性上升,而撑杆力Fe变化趋势较小,更节能。
为了验证 M g M b表达式的科学性和合理性,严格依据原车型的空间位置进行建模,进行仿真验证。仿真模型详细考虑了尾门动作中的关键部件,包括车身安装位置、车门本体、铰链、2个车身支架和2根撑杆。
为了实现尾门开闭全过程的仿真,关键部件需按照实际装配方式进行连接设置。模型的装配方式可分为以下4种:
(1)刚性连接:铰链以及2个车身支架其相对车身在ZYX三轴的旋转和位移都需要进行约束,因此应为刚性连接。
(2)旋转连接:铰链组件内部通过销钉进行连接,如图5中的1所指位置。
(3)球连接:自由度在ZYX三轴的旋转不受约束,仅约束ZYX三轴的位移,车身点B为车身支架与撑杆球头连接装配如图5中的2、3所指位置;尾门点A为尾门球头与撑杆球头连接装配如图5中的4、5所指位置。
(4)平移连接:撑杆组件在车门开闭过程中需要在伸缩行程内进行平移,如图5中的6、7所指位置。
内部阻力主要来源于阻尼盒的静态扭矩。阻尼盒的结构如图6所示,相关参数包括:阻尼盒的挤压弹簧力 N = 130   N,摩擦片与紧固片的摩擦因数 μ = 0.2,弹簧直径 d = 19   m m,阻尼静态扭矩公式为:
$T=N \times d / 2 \times \mu$
式中: T为阻尼静态扭矩, N为挤压弹簧力, d为弹簧直径, μ为摩擦因数。计算得出阻尼静态扭矩 T = 247   N · m m
仿真需要输入阻尼系数 C,已知丝杆导程 P = 15   m m,即丝杆每转一圈丝杆推动撑杆移动 15   m m。撑杆由最短伸至最长行程为 150   m m,开门和关门均在 4   s内完成,因此撑杆的移动速度为 37.5   m m / s,转换成每秒电机转的圈数 2.5   r a d / s。丝杆旋转速度 V、阻尼系数 C、撑杆内部阻尼力 f分别为:
$V=2 \pi \times \frac{d}{2} \times \frac{\mathrm{rad}}{\mathrm{~s}}$
$C=\frac{T}{2 \pi} \times \frac{d}{2} \times V$
$f=2 \pi \times T / P$
式中: V为丝杆旋转速度, d为弹簧直径, C为阻尼器的阻尼系数, T为阻尼静态扭矩, f为撑杆内部阻尼力, P为丝杆导程。计算得出 V = 149.23   m m / s C = 15.72   N · s / m m f = 103.468   N
仿真设定参考原车弹簧力,设定初始弹簧力(即电动撑杆最长行程处弹簧力)为400 N。弹簧最大力值为850 N。根据电动撑杆行程150 mm,结合胡克定律 F = K × L,计算得弹簧系数K约为3。车门质心坐标及转轴至质心距离长度测量参数见表1,设计加配重为27.27 kg,与原车尾门质量称重27.31 kg相近,确保仿真模型的准确性。
在开关门全程, Δ M影响PLG系统开关门性能以及悬停功能。通过在仿真模型中测量得到以下参数。
M g表达式中,输入表2参数。
通过 M g表达式计算在尾门最大位置时 M g = 162.4   N · m
M b表达式中,输入表3参数。
通过 M b表达式计算尾门最大位置时 M b = 287.82   N · m Δ M = M b - M g = 125.44   N · m,尾门边缘点顶端距离旋转轴距离 L = 1   109.14   m m,根据 F = M / L,此时的操作力 F = 113.1   N
尾门处于最高位置的 Δ M相当于此时尾门的操作力。通过2.3小节计算得出操作力 F与CAE仿真软件计算的最高位置保持力对比,可以验证 M b M g的表达式合理性。
通过CAE软件对仿真模型进行运动仿真见图7,得出操作力 F = 113.8   N
电动尾门在出开门最大位置时,操作力为 F = 113.1   N,与仿真计算高度吻合(0.7 N的误差),也验证了 M b M g的表达式以及 Δ M的计算表达式的科学合理。
本研究围绕SUV汽车电动撑杆的动态力学特性展开,通过理论建模与仿真验证相结合的方法,系统分析了尾门开闭过程中力学行为的关键影响因素,并得出以下结论:
(1)力学模型建立与动态关系推导:通过简化约束条件(忽略摩擦、对称性假设等),建立了基于X-Z平面投影的二维力学模型;推导了撑杆长度、力臂与尾门开启角度的动态关系,揭示了重力力矩 M g与撑杆力矩 M b随角度变化的规律。
(2)动态性能优化方向:通过调节弹簧力与电机力的协同作用,平衡悬停功能(需较大 M b)与操作轻便性(需较小 M b)的优化策略;优化弹簧刚度系数以降低能耗,提升系统能效。
(3)仿真验证与模型精度:仿真验证表明,理论模型与实测结果高度吻合,最大操作力误差较小,验证了 M b M g表达式的科学性与实用性。
相较之前的研究,本文研究创新点总结如下:
(1)动态角度参数化建模:通过动态角度参数化建模,明确了θ对撑杆力与力矩的非线性影响,弥补了动态过程量化不足的缺陷。
(2)引入动态力学概念:修正了传统模型中固定力臂的假设,更贴合实际工况。
(3)阻尼系数与内部阻力的耦合计算:通过引入阻尼系数与内部阻力的耦合计算,完善了撑杆动态阻力模型,提升了仿真精度。
但当前模型未考虑撑杆内倾角、多向振动等复杂因素,可能影响极端工况下的预测精度,未来可就此方向进一步研究,以提升模型的普适性与鲁棒性。
综上,本研究为电动尾门撑杆系统的设计与优化提供了理论依据与工程指导,其动态建模方法与仿真验证框架可拓展至其他汽车铰链机构的力学分析中。
  • *国家自然科学基金项目(52076141)
  • 湖南省自然科学基金资助(2023JJ50262)
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doi: 10.19822/j.cnki.1671-6329.20240152
  • 首发时间:2025-10-29
  • 出版时间:2025-06-05
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*国家自然科学基金项目(52076141)
湖南省自然科学基金资助(2023JJ50262)
作者信息
    1 邵阳学院,邵阳 422000
    2 中汽研汽车检验中心(广州)有限公司,广州 511340

通讯作者:

袁文华,教授,博士,主要研究方向为内燃机节能与排放控制,
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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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