The Simulation tools applied to high frequency NVH issues session will take place on Wednesday May 18th and will be chaired by Torsten Treyde of ZF Group and co-chaired by Jay Fash of Zoox.
Topics and speakers for the session include:
Fast CEA computations for brake NVH using machine learning
Merten Stender, tensorDynamic GmbH
Complex eigenvalue analysis (CEA) is a conventional evaluation tool in virtual brake system development for improved noise, vibration and harshness (NVH) characteristics. The discretization of full-scale brake systems, using a quarter-car model, results in millions of finite elements for which the linearized dynamic vibration analysis of CEA is carried out. Hence, the calculation of all eigenvalues across a wide frequency range for a sample space of possible operational parameters during a brake procedure regarding brake pressure, rotational velocity and coefficient of friction is compute-intense and time-consuming.
This study presents a machine learning approach to compute the complex eigenvalues between 1 kHz and 5 kHz for a FE model of a disc-pad setup for a given load configuration in terms of disc rotation velocity, brake pressure and coefficient of friction. Training data are generated through a design-of-experiments study using latin hypercube sampling and a classical CEA solver. Using XGBoost machine learning approaches, we illustrate that mode-coupling instabilities can be represented successfully by the ML model for new and unseen load parameters. The near-real-time capabilities of the ML models are shown to pay off against the offline costs for training data generation, hence rendering the ML approaches particularly relevant for repetitive computations.
Using deep learning to identify the evolution of contact localization and the consequence on the friction-induced vibration
Nikzad Motamedi, University of Lille
In friction brakes, the contact interface is highly scalable with changing contact locations during braking. This evolution is crucial to the performance of the system such as particle emission, noise generation, squeal, etc. The prediction of the contact evolution is then a challenge that it is essential to take up to better understand the phenomena and thus to better control them. A state-of-the-art review considers some models exist to predict this evolution [1,2,3]. Nevertheless, these models are often not predictive with respect to the experimental truth due to the difficulty of contact access. In this paper, a model for predicting the localization is proposed with the experiment as a starting point.
One signature of the contact state is the temperature field. To this end, a pin-on-disc test [4] was heavily instrumented with 6 thermocouples that were uniformly distributed in the brake lining near the surface. More precisely, a campaign of nearly 600 tests was carried out with variable input parameters (disc speed, braking time etc.). All of this data are used to establish a prediction model of the contact evolution regardless of the configuration, even if it does not exist in the initial database.
In this work, we propose an artificial intelligence approach via a Deep Recurrent Convolutional Neural Network (DRCNN) architecture, and by considering a memory effect over a short period. At the end of this model and according to the first instants of contact (less than one second), a prediction of the evolution of the various thermocouples is proposed on a contact which can go beyond 30s. The methodology shows its effectiveness regarding configurations for tests that were not included in the learning base (20% of the 600 tests). Even very local phenomena on each thermocouple are predicted with results of less than 5% error.
Based on this prediction of the contact location for all instants, another artificial intelligence scheme is proposed downstream to predict the dynamic behaviour on target squeal frequencies. Again, the results are convincing with a good correspondence of the model results with the experimental results.
In conclusion, the proposed strategy shows an indisputable link between the localization that can now be predicted and the vibratory behaviour. Moreover, by inverse method, the most influential factors have been identified allowing to foresee the possibility of medium-term power for the industrialists to optimize the system by reworking the initial surface condition for example. Finally, the obtained results show, the contact mechanism can be clearly explained, and this problem can be solved. Also, noise pollution can be greatly reduced, and the environment condition can be improved.
[1] Y. Waddad, V. Magnier, P. Dufrénoy, G. De Saxcé, A multiscale method for frictionless contact mechanics of rough surfaces, Tribology International, Volume 96, 2016, Pages 109-121, ISSN 0301-679X, DOI: https://doi.org/10.1016/j.triboint.2015.12.023.
[2] M. Mueller, G.P. Ostermeyer, Cellular automata method for macroscopic surface and friction dynamics in brake systems, Tribology International, Volume 40, Issue 6, 2007, Pages 942-952, ISSN 0301-679X, DOI: https://doi.org/10.1016/j.triboint.2006.02.045.
[3] M. Stender, M. Tiedemann, D. Spieler, D. Schoepflin, N. Hoffmann, and S. Oberst, “Deep learning for brake squeal: Vibration detection, characterization and prediction,” arXiv, 2020.
[4] M. Duboc, V. Magnier, J-F. Brunel, P. Dufrénoy, Experimental set-up and the associated model for squeal analysis Mechanics & Industry, 21 2 (2020) 204, DOI:https://doi.org/10.1051/meca/2019083
Disc brake squeal: influence of disc - friction material contact localizations
Nicolas Strubel, Hitachi Astemo
Squeal in disc brake systems are powerful acoustic emissions involving significant environmental pollution and client complaints. Recent experimental and numerical results have shown that it could be possible to investigate influence of contact localizations at pads/disc interfaces on squeal behaviour, by considering geometry variations linked to load bearing area modifications, and friction material impact on tribological circuit. In this research project, numerical simulations and experimental aspects at different scales are of interest, the purpose being to identify key parameters to introduce into multiscale simulations.
The study is focused on macroscopic influent parameters, keeping in mind that microscopic scale also has an impact on squeal behaviour.
A full-scale brake system provided by Hitachi Astemo is tested on a dynamometer bench with a dedicated NVH squeal matrix, and various pads geometric configurations are considered, in order to characterize acoustic emissions. Different squealing patterns are observed when changing geometries, giving consequently an industrial base than can be further analysed via a laboratory simplified configuration. A full-scale numerical model of the industrial brake is then used with Complex Eingenvalue Analyses (CEA) simulation type, having been correlated to experimental results.
CEA results show that unstable frequencies are different considering pads geometries. Particularly, regarding type of geometric modification (parallel or radial chamfers, central slots, and mix of these cases), instable frequencies are not the same when really implementing these modifications or when assuming contact zone as the projection of these geometric changes. Therefore, it involves that pure interface contact influence can have a major effect on squeal depending on type of modification applied on pads lining.
To study more finely contact evolution and acoustic emissions, a pin-on-disc system is then considered, equipped with a multimodal instrumentation and an in-operando surface tracking. It allows to continuously track assumed contact zone and surface evolution at pin/disc interface through braking sequences, thanks to thermal measurements via an inserted thermocouple film. Information on macroscopic contact localizations can thus be interpreted with help of a thermomechanical numerical model and CEA simulation of the pin-on-disc configuration.
It is observed that macroscopic localizations indeed have an impact on squeal frequencies and evolve through time namely because of thermal expansion and wear accumulation.
In the future, a deeper investigation on pads geometries and lining formulations will help understanding the mechanisms involved in disc brake squeal, by namely implementing defined key parameters, linking input characteristics to instable / squealing frequencies properties.
Brake squeal optimisation: Novel approach to shift specific eigenfrequencies as independently as possible
Marcel Deutzer, Volkswagen AG
Brake squeal is a well-known phenomenon in disc brakes induced by the mode coupling effect. The complex eigenvalue analysis (CEA) is widely used to identify this phenomenon by calculating the complex eigenvalues in a given frequency range. The real part of the eigenvalues is a measure for unstable oscillations corresponding with the probability of brake squeal. In various recent researches, attempts have been made to reduce the brake squeal propensity by avoiding mode coupling, e. g. by increasing the system damping or by shifting the frequencies of coupling-critical eigenmodes. The latter is a problematic task, as structural modifications often effect other non-involved eigenmodes and may cause unwanted effects. In this study, a novel heuristic approach is presented to shift the frequency of a specific eigenmode by structural modification and constraining other eigenfrequencies simultaneously. First, the complex eigenvalue analysis of a disc brake delivers the critical eigenmodes. The calculation of component contribution factors (CCF) and component mode contribution factors (CMCF) reveals the brake component and the corresponding eigenfrequency with the strongest influence onto the unstable oscillation. Secondly, the new approach is applied to the chosen brake component. The results show the potential of the new method and its limitations. Experimental investigations emphasize the effectivity of the numerical approach.
Parameter study by built-in high-performance sampling for simulation of brake squeal
Michael Klein, INTES GmbH
Numerical method procedures for brake squeal analysis are widely accepted in industry. Using simulations in an early design stage reduces time to market, saves costs, improves the physical behaviour of the brake system, and makes it possible to reduce physical prototypes.
By reducing the number of prototypes, the importance of the simulation is constantly increasing. The simulation must cover the entire range of conditions of the component to guarantee a reliable function in every state. This requires varying as many parameters as possible over a wide range and checking all combinations to identify unfavourable combinations. It follows that the number of variants increases, and the run time of the simulation becomes more important.
Built-in sampling is the key feature to organize the growing number of variants. Sampling is used to cover brake behaviour for variation of parameters in wide ranges. To provide a tool that is as general as possible, the limitations in the selection of parameters as they existed up to now must be overcome by new methods. So far, either methodological reasons or simply the run time have limited the selection of possible parameters.
New developments make it possible to also select the parameters with influence on the results of the non-linear contact analysis. Mainly these are the brake pressure and the coefficient of friction. For performance reasons, the user is still able to select the appropriate scope of the analyses to be repeated for each parameter so that no unnecessary calculation parts are carried out.
The sampling of brake pressure and friction coefficient is shown using an industry-oriented brake model. Both, the performance aspects, and the benefits of the results are shown and assessed.
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