Tire Performance Prediction Using Elasto-Plastic Snow Model
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Solution Overview
Problem
Current tire performance prediction methods on snowy road surfaces face inefficiencies due to the non-linearity of snow properties, such as volume compaction and shear strength, which are difficult to accurately model using existing numerical analysis techniques, leading to inefficient tire designing-evaluation cycles.
Innovation Solution
A tire performance prediction method that models snow as an elasto-plastic body, representing non-linearity in volume compaction using a piecewise-linear continuous function and shear properties with a linear function based on pressure, allowing for precise simulation of tire performance on snowy road surfaces by creating a snow model through indoor testing and three-dimensional image analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If snow is modeled using existing numerical analysis techniques, then the simulation can be performed, but the prediction accuracy is insufficient due to the non-linearity of snow properties
Solution Approach 1:
The snow model segments the non-linear stress-strain relationship into multiple linear segments. The stress-strain curve is divided into distinct regions (elastic region, plastic region, compaction region) with different linear characteristics, allowing accurate representation of snow's non-linear behavior while maintaining computational tractability through piecewise-linear functions
Solution Approach 2:
The model changes parameters based on stress conditions. Different material parameters (elastic modulus, Poisson's ratio, yield strength) are applied depending on the stress level and state. The model transitions between different parameter sets as the snow undergoes phase changes from elastic deformation to plastic deformation to compaction, accurately capturing the stress-dependent behavior of snow
2Measurement precision
If prototype testing is used to evaluate tire performance, then actual performance data is obtained, but the development cycle is lengthy and inefficient
Solution Approach 1:
The invention creates a virtual copy of the physical tire-snow interaction system through numerical simulation. A detailed finite element model of the tire and the snow model replicate the physical behavior, allowing performance evaluation without physical prototypes. This virtual copying enables multiple design iterations to be tested computationally, dramatically reducing the time required for tire development while maintaining prediction accuracy
Solution Approach 2:
The snow model and tire model are prepared in advance with pre-defined material properties, geometric parameters, and boundary conditions. The simulation framework is established beforehand, allowing rapid evaluation of different tire designs by simply changing input parameters rather than setting up entire physical test scenarios each time, thus accelerating the design iteration process
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
This approach improves the accuracy of tire performance prediction on snowy surfaces, enabling more efficient tire designing-evaluation cycles by accurately capturing the complex properties of snow, resulting in closer alignment with actual measurement results.
Implementation Method 1
the snow model represents non-linearity of a volume compaction property of snow by a relation between a density of the snow or a volume strain of the snow and a pressure on the snow
Implementation Method 2
the snow model represents a shear property of the snow by a relation between a yield stress of the snow and a pressure on the snow
Implementation Method 3
the performance of a tire on a pavement surface can be obtained through simulation by performing analysis on the load applied by the tire to a rigid road surface and the rolling motion of the tire
Data Source
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AI summary
Disclosed is a method for predicting tire performance in which a tire model, which comprises a tread pattern capable of imparting deformation by means of ground contact and/or transfer, and a snow model, in which a snow-covered road surface that comes into contact with the tire model is represented, are used to predict tire performance on the snow-covered road surface on the basis of physical quantities that occur in at least either of the tire model and the snow model. The snow model is modeled as an elasto-plastic body or an elastic body, the nonlinearity of the volume compression property of snow is represented by the relationship between the density or volume strain of the snow and the pressure of the snow, and the shear property of the snow is represented by the relationship between the yield stress of the snow and the pressure of the snow.