【作者】 曹友强；

【导师】 邓兆祥；

【作者基本信息】 重庆大学 ， 车辆工程， 2011， 博士

【摘要】 随着汽车产量和保有量的增加,节能、环保、安全业已成为当代世界汽车技术发展面临的重要问题,而在新能源路线不明朗的形势下,汽车轻量化技术则成为全球主流汽车企业应对这一问题的最佳解决途径。汽车车身作为汽车的重要组成部分,是汽车实现轻量化目标的关键部位。然而,当汽车轻量化车身壁板变薄后,必然导致结构出现低刚度、柔性增大,模态密集度高等特点,这不可避免的将带来车身结构动态性能和NVH性能恶化的现象。在这种情况下,采用常规的NVH控制手段往往受到被动阻尼技术和主动阻尼技术缺点的限制而达不到理想的减振降噪效果。本文在这样的背景下,借鉴机敏约束层阻尼(Smart Constrained Layer Damping ,SCLD)结构在薄壁板件振动主动控制方面的优良性能,深入探讨SCLD结构在车身结构振动噪声控制中的潜力,开展以SCLD结构为基础的轻量化车身NVH性能的主动控制基础研究,从而开发出创新的NVH解决方案,为将来开发高档、高品质轿车开辟新路径。本文首先以车身结构抽象物理模型-板结构为出发点,研究了SCLD减振板的动力学模型的建立。建模中考虑到SCLD结构各层间的耦合运动及位移协调关系,以及压电材料的机电耦合效应,以ADF模型表征粘弹性材料随温频变化的力学特征,并与有限元方法相结合,基于Hamilton原理导出了全新的SCLD耦合系统的动力学分析模型。通过算例及模态实验研究表明:所建立的模型能较准确的反映出SCLD板结构的动力学特性。针对ADF模型与有限元结合的SCLD耦合系统动力学模型自由度庞大的问题,在状态空间域提出了复模态截断法与内平衡降阶法相结合的联合降阶法。基于该降阶方法获得了自由度维数低、具备可观性、可控性特点的动力学模型。算例计算表明了提出的降阶法准确可行,所得的降阶模型可直接用于后续控制系统的开发设计。以局部覆盖SCLD结构的薄钢板为研究对象,分别采用最优控制理论及自适应前馈滤波算法设计了主动控制器,并进行了理论仿真分析。基于自适应主动控制系统,对SCLD薄钢板结构的振动控制问题进行了实验研究。研究证明:SCLD结构具有良好的作动能力和较强的振动响应抑制能力;基于自适应前馈滤波算法的SCLD结构自适应控制器自调节能力较强,具有良好的动态跟踪特性和鲁棒性。随后,建立了SCLD系统辐射声功率预测模型,基于数值方法,开展了SCLD薄钢板结构辐射能力及其影响因素研究。数值计算表明:SCLD结构可以有效降低结构的声辐射,能弥补被动约束阻尼(PCLD)结构对低频辐射噪声控制的不足;SCLD结构阻尼层厚度、粘接层厚度以及压电层厚度变化对结构的动力特及声辐射控制有影响,其中,粘接层、压电层厚度变化影响较大。为实现SCLD技术从简单结构走向复杂振动系统,研究了基于动态神经网络的SCLD结构辨识理论。首先,在多层前馈神经网络LMBP算法基础上,提出了网络学习速率自适应调整的动态训练快速算法-ILMBP算法,并将这种算法在神经网络学习及线性系统、非线性系统的模型辨识中进行了尝试。大量研究结果表明了本文提出的ILMBP算法不仅具有良好的辨识性能,而且能提高神经网络学习的收敛速度。其次,运用基于ILMBP算法的动态神经网络NARX模型实现了SCLD板结构的控制系统离线辨识,并建立了基于辨识模型的SCLD板结构自适应控制器。研究结果表明,基于ILMBP算法的NARX网络模型可获得精度较高的辨识模型。该模型能真实的再现系统的动态特性,可直接用于结构主动控制器仿真分析,且所得的控制器参数能直接用于现场实验。最后,基于前述研究结论,以某轿车车身缩尺模型为实验对象,建立了SCLD车身结构振动噪声自适应主动控制系统,搭建了SCLD车身结构振动噪声硬件在环主动控制试验平台。在不同外扰激励下,开展了基于SCLD技术的车身结构振动噪声主动控制实验,取得了令人满意的效果。其中,在低频单一谐波激励下,施加控制后车厢内振动噪声降低了7.6dB(A);在低频复杂周期信号激励下,施加控制后车厢内振动噪声降低了5.1 dB(A),并且作用于SCLD结构的驱动电压都能低于150伏。从而在实验上证明了SCLD结构能在较低的能量驱动下有效改善车身结构低频的NVH性能。这为SCLD技术的进一步工程应用奠定了良好的基础。更多还原

【Abstract】 As the increasing of the production and quantity of the cars, energy economy, environment protection, safety have been the important problems for the auto technology’s development. Under the situation of the noncommittal way of the new energy, the car lightweight technology which used by the global main auto enterprise, will be the best way to solve the problem before. Car body, as the most important constitution of the car, is the key position to attain the lightweight target of the car. However, when the car body becomes thin, the body structure’s rigidity becomes smaller, the flexibility becomes bigger, and the modal concentration becomes higher, which lead to the deterioration of dynamic performance and NVH performance for the body structure. For this situation, the conventional NVH control method, which used to be restricted by the shortcoming of the passive and active damping technology, can’t reach the ideal damping effect. At this background, learning from the good performance of Smart Constrained Layer Damping (SCLD) structure on the active control of the sheet metal’s vibration, the potential of SCLD structure on vibration and noise Control of Car Body is further discussed. The active control fundamental research of the lightweight body’s NVH function based on the SCLD structure is done.It can not only develop new NVH solution, but also open new path to development of high grade, high quality cars for the future. .Firstly, the establishment of dynamic model is researched for the SCLD plate which is the abstract physical model of the car body. In the modeling, the coupling motion and displacement compatibility of layers and the electrical and mechanical coupling effect of piezoelectric materials are considered. The constitutive property varied with frequency and temperature for viscoelastic material is characterized by ADF model. Then combining with the finite element method, a new coupling dynamic analysis model is derived based on the Hamilton principle. The results of the numerical examples and modal analysis experiments show that the model can accurately reflect the dynamic characteristics of SCLD plate. Due to the confine of ADF model and FEA method, SCLD coupling structure’s dynamic model is faulted for its giant DOF, a new model reduction method composed of the complex modal truncation method and the internal balanced order reduction method proposed in the state space. The dynamic model with low DOF, considerable and controllable characteristics is derived based on the method above. The results of the examples indicate that the proposed reduction method is feasible and the reduced model can be directly applied to the development of the follow-up control system.Regarding thin steel plate with partially covered SCLD structure as the research object, the active controllers are designed respectively based on the optimal control theory and the adaptive feed forward filtering algorithm, and simulation analysis is accomplished. Then, based on the adaptive active control system, the vibration control problem of the thin steel with SCLD structure is researched by experiment. It shows that the SCLD structure has good actuator ability and strong vibration response inhibitory ability; the adaptive controller of SCLD structure owns strong self-adjustment ability, good dynamic tracking characteristics and robustness. Then a radiated acoustic power forecast model of the SCLD system is established. Based on the numerical methods, the radiation ability and its influencing factors of sheet steel with SCLD structure are investigated. The research shows that the SCLD structure can not only effectively reduce the acoustic radiation of the plate, but also can make up for PCLD structure on the low frequency noise control; the damping layer thickness, thickness of splicing layer and piezoelectric layer thickness of SCLD structure have effect on the structural dynamic characteristics and acoustic radiation control, especially the splicing layer thickness and piezoelectric layer thickness.In order to apply SCLD technology from simple to complex vibration system, SCLD structure theory is studied based on dynamic neural network. Firstly,based on LMBP algorithm of multilayer feed forward neural network, an adaptive adjust fast algorithm on dynamic training for network learning rate is put forward, named ILMBP algorithm. Then the algorithm is test on neural network learning, linear system identification and nonlinear system identification. By a large number of researches, it shows that the algorithm which put forward before not only has good recognition performance, but also can improve the convergence speed of neural network learning. Then,the offline identification of control system for SCLD plate is realized by NARX neural network model which using ILMBP algorithm. Then adaptive control system based on identification model is set up. The results show that the NARX network model which based on ILMBP algorithm can obtain higher accuracy of identification model and can really represent the dynamic behavior of the system. It can be directly applied to the simulation analysis of active controller and the parameters of the controller can be directly used in the field experiments. Finally, based on the conclusion of the study before, taking the body scale model of a car as the experimental object, an adaptive active control system for vibration and noise of SCLD body structure has been build. The hardware online platform of active control experiment for vibration and noise of SCLD body structure has also been established. Under different external disturbance excitation, the active control experiments on body structure are carried out based on the SCLD technology, and the satisfactory results have been obtained. Among them, under single harmonic excitation with low frequency, the interior vibration and noise of the car has reduced 7.6dB (A) after control; as well as under the complex periodic signal excitation with low frequency, the interior vibration and noise of the car has reduced 5.1 dB(A) after control, and the driving voltage on SCLD structure is all smaller than 150 volt . Thus it can be proved that SCLD structure can effectively improve the NVH performance of car body structure with low frequency in lower energy. It also can lay a good foundation for further engineering application.更多还原