Lubricants for Metal Belt Continuously Variable Transmissions

Narita, Keiichi

doi:10.3390/lubricants2010011

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…To that end, lubricating oils known as CVT fluid (CVTF) play an important role. CVTFs usually consist of a base oil and various kinds of lubricant additives 3 , 4 . Among these additives, phosphorus- and sulfur-based extreme pressure (EP) additives and calcium-based detergents influence the friction properties at the metal-to-metal contacts between the CVT belt and pulleys.…”

Section: Introductionmentioning

confidence: 99%

Application of a neural network model in estimation of frictional features of tribofilms derived from multiple lubricant additives

Noma,

Aoki,

Kobayashi

2024

Sci Rep

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In the field of tribology, many studies now use machine learning (ML). However, ML models have not yet been used to evaluate the relationship between the friction coefficient and the elemental distribution of a tribofilm formed from multiple lubricant additives. This study proposed the possibility of using ML to evaluate that relationship. Friction tests revealed that, calcium tribofilms formed on the friction surface, with the friction coefficient increasing as a result of the addition of OBCS. Therefore, we investigated whether the convolutional neural network (CNN) model could recognize the tribofilms formed from OBCS and classify image data of the elemental distributions of these tribofilms into high and low friction-coefficient groups. The CNN model classifies only output values, and it’s difficult to see how the model has learned. Gradient-weighted class activation mapping (Grad-CAM) was performed using a CNN-based model, and this allowed the visualization of the areas important for classifying elemental distributions into friction coefficient groups. Furthermore, dimension reductions enabled the visualization of these distributions for classification into the groups. The results of this study suggested that the CNN model, the Grad-CAM, and the dimension reductions are useful for evaluating frictional features of tribofilms formed from multiple lubricant additives.

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Section: Introductionmentioning

confidence: 99%

Application of a neural network model in estimation of frictional features of tribofilms derived from multiple lubricant additives

Noma,

Aoki,

Kobayashi

2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…These additives directly adsorb on the steel surfaces or cause tribochemical reactions under boundary lubrication conditions, forming a boundary film referred to as tribofilm on the sliding surface of the metal [2][3][4]. In order to provide a higher CVT transmission efficiency, it is effective to form a tribofilm with higher friction coefficient [5][6][7]. Tricresyl phosphate (TCP) is an effective antiwear additive generally contained in commercial CVT fluids.…”

Section: Introductionmentioning

confidence: 99%

Correlation between Tribofilm Formation and Friction Coefficient in Continuously Variable Transmission at the Initial Stage of Rubbing

et al. 2019

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To improve the transmission efficiency of a continuously variable transmission (CVT) system, it is effective to form a tribofilm with higher friction coefficient. Therefore, understanding of the correlation between the tribofilm formation and friction coefficient in a CVT fluid has been a great deal. In this study, the tribofilm formation on a bearing steel ball surface under the simulated additive oil was investigated. We used ball-on-disk tribological test and optical microscopy imaging to observe the temporal changes in the tribofilm growth. Atomic force microscopy and energy-dispersive X-ray spectrometry analyses revealed that the tribofilm consisted of pad-like structures derived by tricresyl phosphate and calcium sulfonate additives. A binary imaging analysis showed that the total area of the pad-like structure was a key parameter determining the friction coefficient. The pads were repeatedly desorbed and reformed during the sliding test. These results improve the design of future CVT systems and lubricants.

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Correlation between pressure-viscosity coefficient and traction coefficient of the base stocks in traction lubricants: A molecular dynamic approach

Lü

Wang

Ren³

et al. 2019

Tribology International

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Lubricants for Metal Belt Continuously Variable Transmissions

Cited by 4 publications

References 9 publications

Application of a neural network model in estimation of frictional features of tribofilms derived from multiple lubricant additives

Application of a neural network model in estimation of frictional features of tribofilms derived from multiple lubricant additives

Correlation between Tribofilm Formation and Friction Coefficient in Continuously Variable Transmission at the Initial Stage of Rubbing

Correlation between pressure-viscosity coefficient and traction coefficient of the base stocks in traction lubricants: A molecular dynamic approach

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