共查询到19条相似文献,搜索用时 234 毫秒
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发动机隔振系统振动固有特性的优化计算及影响因素分析 总被引:1,自引:0,他引:1
对发动机隔振系统振动固有特性进行了理论分析,引入了六自由度能量解耦理论,依托Matlab的矩阵运算能力,开发了发动机隔振系统优化设计软件,并利用该软件对系统进行了振动固有特性分析和能量解耦优化。考虑到悬置元件刚度的实际值与设计值可能存在一定偏差,因此针对某解耦度较高的系统,按照悬置元件各向刚度参数±20%的偏差范围,对系统进行仿真试验,研究了悬置元件刚度偏差对系统振动固有特性的影响,所得结论对隔振设计和悬置元件的工艺控制具有一定的指导意义。 相似文献
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合理设计发动机悬置元件可以明显地降低汽车的振动和噪声,改善汽车的乘坐舒适性。文中分别用Matlab中的 Pareto 算法和 Isight 多目标优化法对发动机悬置元件刚度进行优化,将优化结果进行对比,得出前者优化后的解耦率较高,优化效果更明显。 相似文献
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动力总成悬置系统解耦设计 总被引:3,自引:0,他引:3
阐述了用于动力总成悬置系统解耦设计的转矩轴理论和能量解耦法,给出了这2种理论的计算方法,并利用这2种方法对某国产汽车的动力总成悬置系统进行了解耦设计,结果表明:将悬置布置在转矩轴上,通过合理设计悬置的刚度可以对动力总成悬置进行很好的解耦设计。 相似文献
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发动机悬置系统优化设计及其可靠性分析 总被引:3,自引:2,他引:1
建立发动机悬置系统6自由度模型,采用能量解耦的方法设定优化目标函数,应用多岛遗传算法进行确定性优化.运用Monte Carlo方法对优化结果进行可靠性分析,并计算解耦灵敏度. 相似文献
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发动机-悬置系统的能量法解耦及优化设计 总被引:15,自引:0,他引:15
本文通过发动机-悬置系统的能量分布得到系统解耦的能量指标,并以该能量指标为优化设计目标。以系统的固有频率为约束条件,应用DSFD算法对系统进行优化计算。所编制的优化设计程序具有计算可靠、收敛速度快的特点。为便于程序应用,本文指出了系统能量解耦目标、频率约束及设计变量等因素对优化计算的影响。对某一轻型货车发动机-悬置系统的优化计算表明,仅通过悬置刚度参数的调整即可使系统的解耦水平明显提高。 相似文献
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在分析各种优化方法优缺点的基础上,建立发动机悬置系统六自由度动力模型。以六自由度方向的解耦率为最大优化目标,以各悬置点三向刚度为设计变量,选用免疫进化算法对发动机的悬置刚度参数进行优化,最后用Monte Carlo法对悬置系统进行稳健性分析。结果表明,优化解不仅能保证六自由度方向的高解耦率,还能保证悬置系统的稳健性,提高了产品的质量。 相似文献
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针对车辆在纵向运动和横摆运动时的强耦合关系给车辆动力学控制带来的困难,以四轮独立电驱动车辆作为研究对象,基于微分几何理论设计了车辆系统运动解耦控制方法,将非线性强耦合的四轮驱动车辆动力学系统解耦为纵向和横向两个相对独立运动控制子系统,并设计了鲁棒控制器,以提高抵抗车辆行驶时不确定外力如侧风的干扰能力。基于 Trucksim 软件建立四轮驱动车辆模型,并针对车辆解耦控制策略和抗干扰策略进行了仿真测试。结果表明,相比于无解耦控制的车辆,采用微分几何解耦控制的四轮独立驱动车辆纵向速度偏差降低了 82.1%,横摆角速度偏差降低了80.7%,且微风干扰下的抗干扰能力明显改善,车辆稳定性显著提升。为验证该运动解耦控制策略在实时系统中的控制效果,还进行了硬件在环试验,结果表明,硬件在环试验的结果与仿真结果一致。 相似文献
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This paper presents a robust optimization design method based on Six Sigma quality control criteria to improve the design
of a powertrain mounting system (PMS). The powertrain is modeled as a rigid body having six degrees of freedom (DOF) connected
to a rigid base by four rubber mounts, and each mount is simplified as a three-dimensional spring-damper element in its local
coordinate system (LCS). The calculation method based on energy decoupling is used to estimate the decoupling ratios of a
PMS. The location and static stiffness of each mount and the orientations of the two anti-torsion mounts are selected as uncertain
design variables, and the nominal values of these design variables are optimized to obtain a robust Six Sigma design for a
PMS. The uncertain design variables are characterized by a perturbation or percent variation around their nominal values.
The generalized reduced gradient (LSGRG2) optimization method is employed to solve the robust optimization problem, and a
second-order Taylor series expansion is used to estimate the statistical properties of the performance constraints and objectives.
The optimization results show that the robust design ensures good robustness or high reliability for the natural frequencies,
decoupling ratios, and frequency separation constraints of a PMS. 相似文献
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T. H. S. Li C. J. Huang C. C. Chen 《International Journal of Automotive Technology》2010,11(4):581-592
A novel tracking and almost disturbance decoupling problem of multi-input, multi-output (MIMO) nonlinear systems based on
feedback linearization and a multi-layered feedforward neural network approach has been proposed. The feedback linearization
and neural network controller guarantees exponentially global uniform ultimate bounded stability and almost disturbance decoupling
performance without using any learning or adaptive algorithms. The new approach renders the system to be stable with the almost
disturbance decoupling property at each step when selecting weights to enhance the performance if the proposed sufficient
conditions are maintained. One example, which cannot be solved by the existing approach of the almost disturbance decoupling
problem because it requires the sufficient conditions that the nonlinearities that multiply the disturbances satisfy structural
triangular conditions, is proposed to exploit the fact that the tracking and the almost disturbance decoupling performances
are easily achieved by the proposed approach. In order to demonstrate the practical applicability, a famous half-car active
suspension system is investigated. 相似文献
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J. Wu 《International Journal of Automotive Technology》2012,13(3):409-422
This paper presents a robust optimization method to decrease the variations in the performance of the designed system caused
by the unavoidable manufacturing, installation or measurement errors of the design variables. Generally, it is difficult and
costly to determine statistical information with sufficient precision for uncertain design variables; in this study, interval
numbers are used to describe the uncertain design variables, and only the bounds of these variables are required. An improved
interval truncation method is presented for estimating the variation ranges of the system performances. The robustness estimations
of the system performances are incorporated into the optimization formulation to obtain the nominal design variables, which
could make the system performances relatively robust; therefore, the design robustness is estimated and improved in the optimization
iteration process. The robust optimization method is applied to a general powertrain mounting system (PMS) to improve the
design robustness of the PMS decoupling layout and frequency allocation. The optimization results show that the robust optimization
method could effectively increase the decoupling ratios in the interested vertical and pitch directions, and the frequency
allocation is more robust than that obtained using the traditional deterministic optimization. 相似文献
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应用稳健优化设计理论,考虑设计变量的不确定性对结果的影响,建立稳健优化模型。以发动机悬置系统能量解耦为目标,用Pareto遗传算法对系统的刚度参数进行稳健优化,并将优化结果运用Monte Carlo方法进行分析.结果表明,优化方法可以有效提高悬置系统的稳健性。 相似文献