Observation and Characterization of Squeak Noises of Polymeric Materials for Automotive Interior Parts Under Field-Degradation

Lee, Changhun; Kang, Byunghyun; Choi, Byoungho; Lee, Jong-Ho; Lee, Kwanghee

doi:10.7467/ksae.2017.25.2.257

Cited by 5 publications

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nam and Kang 5 studied the effect of sliding speed and normal load on the squeak noise of aluminum and steel using the pin-on-disk test. Lee et al 6 analyzed field-degraded polypropylene-copolymer-based automotive interior parts using Fourier transform infrared spectroscopy and evaluated changes in mechanical properties and the squeak noise resulting from degradation. Nam et al 7 studied the squeak noise from lubricated surfaces using a reciprocating friction tester.…”

Section: Introductionmentioning

confidence: 99%

Experimental study on the factors affecting squeak noise occurrence in automotive suspension bushings

Kang

Choi

Sung

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

Self Cite

View full text Add to dashboard Cite

In this study, friction tests are performed, via a custom-built friction tester, on specimens of natural rubber used in automotive suspension bushings. By analyzing the problematic suspension bushings, the eleven candidate factors that influence squeak noise are selected: surface lubrication, hardness, vulcanization condition, surface texture, additive content, sample thickness, thermal aging, temperature, surface moisture, friction speed, and normal force. Through friction tests, the changes are investigated in frictional force and squeak noise occurrence according to various levels of the influencing factors. The degree of correlation between frictional force and squeak noise occurrence with the factors is determined through statistical tests, and the relationship between frictional force and squeak noise occurrence based on the test results is discussed. Squeak noise prediction models are constructed by considering the interactions among the influencing factors through both multiple logistic regression and neural network analysis. The accuracies of the two prediction models are evaluated by comparing predicted and measured results. The accuracies of the multiple logistic regression and neural network models in predicting the occurrence of squeak noise are 88.2% and 87.2%, respectively.

show abstract

Section: Introductionmentioning

confidence: 99%

Experimental study on the factors affecting squeak noise occurrence in automotive suspension bushings

Kang

Choi

Sung

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

Self Cite

View full text Add to dashboard Cite

show abstract

“…Steel sheets for automobiles are exposed to various corrosive environments due to climate change. In particular, the increased inundation from heavy rain and the use of salt for snow removal accelerate the corrosion of the automobile steel sheet, which leads to the deterioration of the durability and the collision safety of the vehicle [ 1 ]. Furthermore, with the recent rapid development of industry, these corrosive environments are becoming more and more severe.…”

Section: Introductionmentioning

confidence: 99%

Effect of Cr on Aqueous and Atmospheric Corrosion of Automotive Carbon Steel

Cho

Yoo

et al. 2021

Materials

View full text Add to dashboard Cite

This study investigated the effect of Cr alloying element on the corrosion properties of automotive carbon steel (0.1C, 0.5Si, 2.5Mn, Fe Bal., composition given in wt.%) in aqueous and atmospheric conditions using electrochemical measurement and cyclic corrosion tests. Three steels with 0, 0.3, and 0.5 wt.% Cr were studied by electrochemical impedance spectroscopy. Polarization resistance (Rp) of 0.3 Cr and 0.5 Cr steels was higher than that of 0 Cr steel, and the Rp also increased as the Cr content increased. Therefore, Cr increases the corrosion resistance of automotive carbon steel immersed in a chloride ion (Cl−)-containing aqueous solution. In the cyclic corrosion test results, Cl− was concentrated at the metal/rust interface in all of the steels regardless of Cr content. The Cl− was uniformly concentrated and distributed on the 0 Cr steel, but locally and non-uniformly concentrated on the Cr-added steels. The inner rust layer consisted of β-FeOOH containing Cl− and Cr-goethite, while the outer rust layer was composed of amorphous iron oxyhydroxide mixed with various types of rust. FeCl2 and CrCl3 are formed from the Cl− nest developed in the early stage, and the pitting at CrCl3-formed regions are locally accelerated because Cr is strongly hydrolyzed to a very low pH.

show abstract