Sliding Surface Roughness Control for Lubricated Friction Estimation
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Solution Overview
Problem
Existing methods fail to accurately estimate sliding friction between lubricated sliding surfaces due to the limitations of using root-mean-square roughness as a parameter for surfaces with biased roughness distributions, leading to inaccurate friction predictions.
Innovation Solution
A method that utilizes a correlation between friction coefficient and an oil film parameter calculated using core portion level difference and reduced peak height to set target surface roughness values, enabling precise control of sliding friction through a friction design and surface roughness control process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If root-mean-square roughness Rq is used as a parameter to estimate sliding friction, then the estimation process is simple, but the estimation accuracy is insufficient for surfaces with biased roughness distributions
Solution Approach 1:
The patent changes the roughness parameter from root-mean-square roughness Rq to core portion level difference Rk and reduced peak height Rpk. These new parameters better represent surfaces with biased roughness distributions and enable accurate friction estimation while maintaining reasonable process simplicity.
2Object-generated harmful factors
If lubricating oil viscosity is increased to increase oil film thickness, then friction in low rotation range is reduced, but fuel consumption increases
Solution Approach 1:
The patent changes the approach from modifying lubricant viscosity to modifying surface roughness parameters. By controlling Rk and Rpk to achieve hydrodynamic lubrication, the system reduces friction without requiring high-viscosity oil, thus avoiding increased fuel consumption.
Solution Approach 2:
The patent substitutes the mechanical approach of increasing viscosity for a surface engineering approach. By optimizing surface topology (Rk, Rpk), the system achieves better lubrication conditions without changing the lubricant's mechanical properties.
3Object-generated harmful factors
If surface roughness is reduced to achieve hydrodynamic lubrication, then friction is reduced, but manufacturing precision requirements increase
Solution Approach 1:
The patent identifies specific target ranges for Rk (0.02-0.5 μm) and Rpk (0.005-0.1 μm) that balance friction reduction with manufacturability. These parameter specifications provide clear manufacturing guidelines while achieving the desired hydrodynamic lubrication condition.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise estimation and control of sliding friction between lubricated sliding surfaces, improving process capability and production efficiency of sliding mechanisms like tapered roller bearings.
Implementation Method 1
making the lubrication conditions between the mutual sliding surfaces of the roller head portions and the large flange portion transition to the hydrodynamic lubrication, in which the sliding surfaces are separated from each other by oil film
Implementation Method 2
lubrication conditions between the sliding surfaces are in the boundary lubrication, in which the sliding surfaces are partially in a solid contact with each other
Data Source
Figure 1
Figure 2~3B
Figure 4A~4B
AI summary
Provided is a friction design method capable of estimating sliding friction generated between mutual sliding surfaces of two sliding members lubricated with lubricant with high precision. The friction design method sets a friction coefficient µ in a sliding surface model corresponding to mutual sliding surfaces of two sliding members (2 and 3) lubricated with lubricant (step S1), and, based on a correlation between the friction coefficient µ and an oil film parameter (Λ(Rk) or Λ(Rk+Rpk)) calculated using a core portion level difference (Rk) or a sum of the core portion level difference (Rk) and reduced peak height (Rpk) as a parameter representing surface roughness in the sliding surface model (step S2), sets a target value for surface roughness of the sliding surfaces required to be controlled as a product (steps S3 to S6).