Brake squeal reduction of vehicle disc brake system with interval parameters by uncertain optimization

Lü, Hui; Yu, Dejie

doi:10.1016/j.jsv.2014.08.027

Cited by 59 publications

(31 citation statements)

References 30 publications

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“…In general, the behavior of the industrial processes and mechanical systems cannot be explained by linear functions [ 19 , 23 , 34 ], so, in the following section, the second-order models (Equation (2)) and the experimental designs that are preferable to adequately estimate these models will be examined.…”

Section: Methods: Design Of Experiments Response Surface Methodolmentioning

confidence: 99%

“…The models developed through the response surface methodology (RSM) are widely used as meta-models [ 17 ]. This methodology is very useful in the design and optimization of new processes and products [ 18 , 19 , 20 ], especially if is affected by several variables, due to its low computational effort. Also, it can be used in an inverse sense, for the system identification applications, to find out the true values of the design variables that are inaccurately defined in a finite element model, with the help of experimental responses.…”

Section: Introductionmentioning

confidence: 99%

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A Consistent Procedure Using Response Surface Methodology to Identify Stiffness Properties of Connections in Machine Tools

et al. 2018

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Accurate finite element models of mechanical systems are fundamental resources to perform structural analyses at the design stage. However, uncertainties in material properties, boundary conditions, or connections give rise to discrepancies between the real and predicted dynamic characteristics. Therefore, it is necessary to improve these models in order to achieve a better fit. This paper presents a systematic three-step procedure to update the finite element (FE) models of machine tools with numerous uncertainties in connections, which integrates statistical, numerical, and experimental techniques. The first step is the gradual application of fractional factorial designs, followed by an analysis of the variance to determine the significant variables that affect each dynamic response. Then, quadratic response surface meta-models, including only significant terms, which relate the design parameters to the modal responses are obtained. Finally, the values of the updated design variables are identified using the previous regression equations and experimental modal data. This work demonstrates that the integrated procedure gives rise to FE models whose dynamic responses closely agree with the experimental measurements, despite the large number of uncertainties, and at an acceptable computational cost.

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Section: Methods: Design Of Experiments Response Surface Methodolmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Consistent Procedure Using Response Surface Methodology to Identify Stiffness Properties of Connections in Machine Tools

et al. 2018

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“…The NESs can therefore dissipate energy over a wide range of frequencies. In the review paper, Lee et al (2008) discus the recent efforts to passively mitigate unwanted vibrations from a primary structure to NESs by utilizing TET.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the dynamic behavior of an uncertain friction system coupled to nonlinear energy sinks using a multi-element generalized polynomial chaos approach

Snoun

Bergeot

Berger

2020

European Journal of Mechanics - A/Solids

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In this paper, a friction system with uncertain parameters and coupled to two Nonlinear Energy Sinks (NESs) is studied. The dispersion of some physical parameters due to their uncertain nature may generate a dynamic instability which leads to a Limit Cycle Oscillations (LCO) causing a propensity of squeal. The concept of Targeted Energy Transfer (TET) by means of NESs to mitigate this squealing noise is proposed. In this kind of unstable dynamical system coupled to NES, the transition from harmless regimes (i.e. the LCO is mitigated) to harmful regimes (i.e. the LCO is not mitigated) as a function of the uncertain parameters implies a discontinuity in the steady-state amplitude profiles. In this context, a Multi-Element generalized Polynomial Chaos (ME-gPC) based method is proposed to locate this discontinuity (called mitigation limit) and therefore to predict the Propensity of the system to undergo an Harmless Steady-State Regime (PHSSR). The results obtained with this original method lead to a good compromise between computational cost and accuracy in comparison with a reference method.

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“…Renault et al [16] investigated brake squeal uncertainty based on finite element model using interval parameter method, and the parameters of working load, damping property effects, material property effects, and pad surface topography effects were treated as uncertain parameters; Sarrouy et al [17] proposed polynomial chaos expansions to study brake squeal uncertainty and the stability of a finite element model of a brake was investigated when its friction coefficient or the contact stiffness was treated as random parameter; Hui Lü proposed a hybrid uncertain model with random and interval parameters to deal with the uncertainties existing in a disk brake system, and Young's modulus of the pad was treated as random parameter [18,19]; Culla and Massi [20] investigated the statistical characteristics of real part of the complex eigenvalue of the system under the assumption that its friction coefficient was random parameter; then a simplified model was established to save computation time; Nobari et al [21] proposed an efficient method of uncertainty propagation via surrogate modeling and then the statistical characteristics of frequency and real part of the complex eigenvalue of an unstable mode were studied; Sarrouy et al [22] proposed two methods based on the polynomial chaos to carry out the stochastic study of a brake squeal and investigated the statistical characteristics of frequency and real part of the complex eigenvalue of unstable mode when friction coefficient and contact stiffness were treated as uncertain parameters, respectively. Former studies show that the uncertainties of friction contact parameters are important causes of frictional squeal uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Influence of Heterogeneous Contact Stiffness and Heterogeneous Friction Coefficient on Frictional Squeal

Zhang

Meng

2018

Shock and Vibration

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Contact stiffness and friction coefficient are excitation sources and key influencing factors to frictional squeal with obvious inhomogeneous characteristic that is always neglected. In this paper, a multipoint contact flexible pin-on-disc system is established considering tangential stiffness. Then influence of contact stiffness and friction coefficient with heterogeneous distribution on frictional squeal is studied using the complex modal analysis. The research shows that contact stiffness and friction coefficient heterogeneities influence the likelihood of occurrence of the squeal, the frequency of the squeal, and the real part of the complex eigenvalue of the system. And when the contact stiffness and friction coefficient are close to the boundary of the region of modecoupling instability, flexible pin-on-disc system with homogeneous contact stiffness and friction coefficient cannot predict whether frictional squeal occurs or not. Besides, uncertain distribution of contact stiffness and friction coefficient can induce the uncertainty of brake squeal.

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Brake squeal reduction of vehicle disc brake system with interval parameters by uncertain optimization

Cited by 59 publications

References 30 publications

A Consistent Procedure Using Response Surface Methodology to Identify Stiffness Properties of Connections in Machine Tools

A Consistent Procedure Using Response Surface Methodology to Identify Stiffness Properties of Connections in Machine Tools

Prediction of the dynamic behavior of an uncertain friction system coupled to nonlinear energy sinks using a multi-element generalized polynomial chaos approach

Influence of Heterogeneous Contact Stiffness and Heterogeneous Friction Coefficient on Frictional Squeal

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