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车辆疲劳耐久性分析、试验与优化关键技术研究
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摘要
车辆中大多数关键零部件的失效都是疲劳破坏。疲劳耐久性作为车辆产品主要性能指标之一,直接关系到车辆安全性、可靠性、经济性,对车辆产品品质和声誉产生重要的影响,因此越来越受到企业以及用户的重视。如何对设计的产品进行疲劳耐久性验证并解决耐久性问题、最终实现耐久性的提升,成为当今车辆技术中的研究热点。在综述车辆疲劳耐久性的研究现状以及存在的不足基础上,本文围绕着车辆疲劳耐久性的CAE分析、道路模拟试验验证、结构抗疲劳优化三个领域进行深入的研究,掌握其关键技术,建立了车辆疲劳耐久性问题的一体化解决方案,为车辆企业的产品研发提供有力的指导和技术支持。本文的研究内容包括以下儿个方面:
     采用预处理和加速编辑方法对整车道路载荷谱进行处理。采用预处理技术,对载荷谱进行毛刺信号剔除、漂移纠正、傅立叶滤波等。通过载荷谱的载荷循环频数、损伤分布分析,确定载荷谱加速编辑的根据,并提出了载荷谱编辑的原则。为了使编辑后的载荷谱在道路模拟试验台上顺利的复现,同时又能节省试验时间,本文提出了兼顾损伤和PSD的载荷谱加速编辑方法,减少了编辑后载荷谱在频域上的失真,促进道路模拟迭代的完成。另外,还提出了载荷谱编辑时针对道路模拟试验台迭代能力欠佳的情况下的解决方法。
     在室内进行道路模拟试验,复现汽车在试验场的各种工况。采用白噪声信号的激励与响应,实现道路模拟的系统识别,并对识别质量进行评价。基于识别的系统频率响应函数,并采用迭代的方式,得到试验台对轮胎的激励信号,保证室内轮胎中心的加速度信号与试验场的目标信号误差足够小。总结了迭代过程中增益系数(gain)的调整等关键技术与注意点。室内试验的故障结果与路试的情况一致,表明道路模拟耐久性试验的有效性。在耐久性试验过程中,还建立了基于动态应变监测及数据统计进行损伤裂纹识别的方法,具有一定的工程应用意义。
     建立整车刚柔耦合多体动力学分析模型,基于模态应力恢复方法和道路模拟物理迭代获得的路面激励,获取上摆臂的动应力响应。采用模态综合法(CMS)分析,得到上摆臂的柔性体模型并获得模态应力结果。利用ADAMS/CAR Ride提供的虚拟四立柱建立了以上摆臂为柔性体的整车刚柔耦合模型。本文提出了基于道路模拟物理迭代获取路面对轮胎的位移激励的方法,并以此激励信号作为刚柔耦合仿真的边界条件,提高了CAE中输入载荷的精确性与有效性,并实现了CAE仿真与道路试验采用同样工况的双重验证。刚柔耦合仿真得到柔性体的各阶模态位移,结合模态应力结果,采用模态应力恢复法得到上摆臂动应力响应。与路试中动应力数据对比,结果表明基于模态应力恢复获取动应力的方法精度高,是一种有效的分析方法。
     针对汽车部分零部件承受非比例多轴载荷,其材料特性与单轴载荷的情况有显著区别,本文对多轴疲劳问题展开研究。建立以下摆臂为柔性体的整车刚柔耦合模型,以道路模拟得到的轮胎激励为边界条件,在虚拟样机中采集轮心处的加速度信号并与试验场原始目标信号对比,验证了刚柔耦合模型的有效性,仿真获取下摆臂各连接点处的载荷谱。采用惯性释放法,获取下摆臂在单位载荷下的应力分布。通过二轴性分析,利用二轴比标准偏差、二轴比时间历程、反映主应力方向的角度Φp的时间历程、二轴比对最大主应力的分布、角度Φp对最大主应力的分布等途径确定下摆臂处于非比例多轴载荷状态。最后,采用Wang-Brown方法进行下摆臂多轴疲劳分析,分析结果与试验场试验结果吻合较好。
     针对车架支架与纵梁连接处的顽固开裂,建立了考虑疲劳寿命的结构优化方法。基于CAE分析得到车架支架的疲劳寿命,以路试结果验证了CAE结果的有效性,为后续的优化设计做好准备。考虑疲劳寿命的约束,进行车架支架结构的拓扑优化,得到材料的合理分布结果。依据该分布结果,设计相应的加强结构。对车架支架、设计的加强结构等板件进行了考虑寿命的尺寸优化。结果表明,结合拓扑优化和尺寸优化两种先进方法,在车架总质量不变的条件下,实现车架支架疲劳寿命大幅度提升。
     针对在复杂结构抗疲劳优化设计中遇到的非线性、计算繁琐、不易迭代等问题,建立了基于近似模型的结构抗疲劳优化设计方法。通过建立参数化模型、拉丁超方法(Latin Hypercubes)实验设计、建立疲劳寿命和体积等的移动最小二乘响应面近似模型、遗传算法(GA)优化求解等过程,得到优化后的结构不仅寿命大幅度提高,而且达到轻量化的效果。
Most key components of the vehicle are damaged because of fatigue. As one of the main performances of vehicle product, fatigue durability is directly related to safety, reliability and economy. and has an important impact on the quality and reputation of vehicle product. Therefore, fatigue durability is paid more and more attention by enterprises as well as the users. How to validate and improve fatigue durability for the products designed becomes a research hotspot. The key technologies of CAE analysis for fatigue durability, road simulation test validation, structure optimization based on anti-fatigue, are studied deeply, and the integrated solutions for the development of vehicle fatigue durability are created. The effective guidance and technical support for the product development of vehicle enterprises are provided. The main work of the dissertation includes the following aspects:
     Road load spectrum of vehicle is pretreated and edited. Spike filter, drift correction, fourier filter are processed by pretreatment technology. The load spectrum is edited according to the frequency distribution and damage distribution of load cycles and the principles of load spectrum editing are put forward. To make the test time short and the edited load history replicated on the road test simulator smoothly, an accelerated load spectrum editing method is advanced considering damage reservation and PSD. Therefore, the distortion in frequency domain is reduced and iterations in road simulation are processed easily. Countermeasure of load spectral editing is put forward when the iteration ability of a simulator is poor.
     To replicate a variety of conditions in proving ground, the indoor road simulation test is carried out. The identification of the FRF (frequency response function) of the simulation system is performed with the white noise drive signals and the corresponding response signals,and the identification quality is evaluated immediately. The iterative process based on the FRF continues until the response errors of acceleration signals at the center of tires converge to an acceptable tolerance level, and the tire excitation signals from the test rig are obtained. The key technologies about gain factor adjustment and other critical points are summed up. It is proved that durability test by road simulation is valid and available by the indoor detected fault results which are in accordance with the road test results. The method of damage and crack identification based on variable strain signal and its statistics is established, and it is meaningful in road simulation test.
     The whole vehicle rigid-flexible coupled model is built to obtain the stress response on upper control arm based on MSR(modal stress recovery) method and road excitation signals from physical iteration results in the road simulation test. The flexible body of upper control arm and modal stress results are gained by CMS (component modal synthesis) analysis. The whole vehicle rigid-flexible coupled model equipped with the upper control arm as a flexible component is built and analyzed on virtual four-poster in ADAMS/Car Ride. The method with which the tire displacement excitations are acquired from the road simulation test is put forward. The rigid-flexible coupled simulation is processed using the tire displacement excitations as the boundary conditions and will improve the accuracy and validity of the input load in CAE. At the same time, this method achieves dual verification between CAE simulation and road test under the same work conditions. The stress responses are received using the modal stress results and the modal displacement histories from rigid-flexible coupled simulation. The CAE results are in accordance with those of road test, so the MSR method is accurate and valid to gain the stress response.
     As many components of vehicle are subjected to the multiaxial loads and their material properties are different from those under the uniaxial load, the multiaxial fatigue theory is researched. To simulate the actual road condition, a drive file which is prepared for dynamics analysis is acquired after the iteration process. The whole vehicle rigid-flexible coupled model is built and is validated with comparison between the acceleration signals at the center of tires in the virtual prototype and the target signals from the proving ground. After analysis, the load histories at the junctions of lower control arm are obtained. The method of inertia relief is used to finite element analysis for the lower control arm. Biaxiality analysis is processed considering the standard deviation of biaxial ratio, the time history of biaxiality ratio, the time history of angle Φp, biaxiality ratio distribution and angle Φp distribution, and determines that the lower control arm is in a non-proportional multiaxial loading state. The multiaxial fatigue life distribution of the lower control arm is achieved with the Wang-Brown method, and the results of multiaxial fatigue analysis are similar to those of proving ground test.
     As the junction between frame bracket and longitudinal beam cracked frequently, the structure optimization method is established considering fatigue life. The frame bracket fatigue life which is validated by the results in road test is analyzed by CAE and is prepared for the subsequent optimization. A reasonable distribution of material is received by topology optimization considering the constraint of fatigue life. According to the distribution result, the strengthened structure is designed accordingly. Size optimization for the frame bracket and the strengthened structure is processed considering fatigue life. The method which combines topology optimization and size optimization, can greatly enhance the fatigue life of the frame bracket, and substantially control the total mass of the frame.
     An anti-fatigue optimal design method based on the approximate model is established as fatigue analysis is a nonlinear, complex question and is difficult to carry out especially when the structure is complicated. With this method, the life of optimized structure is greatly improved and the effect of lightweight is achieved after DOE (design of experiments) by Latin Hypercubes method, foundation of approximation model of fatigue life and volume with moving least squares response surface and optimization solution by GA (genetic algorithm).
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