Tire Contact Patch Monitoring With Low-Frequency Statistical Sampling
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Solution Overview
Problem
Current tire monitoring systems face challenges in accurately estimating the length of the contact area between a tire and the rolling surface, particularly at high speeds, due to the need for sophisticated hardware with high sampling frequencies, leading to increased power consumption and complexity.
Innovation Solution
A statistical approach using low-frequency sampling of tire deformation data, such as radial acceleration, to estimate the probability of the monitoring unit being in the contact area, allowing for real-time monitoring with less expensive and power-efficient systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high sampling frequency is used to accurately detect tire deformations, then measurement precision is improved, but power consumption increases and device complexity increases
Solution Approach 1:
The patent applies partial action by using low-frequency sampling that is insufficient for direct reconstruction of the deformation profile, but sufficient for statistical estimation of contact area parameters. Instead of continuously sampling at high frequency to capture every detail of tire deformation, the system samples sparsely and uses statistical methods to derive the necessary information, thereby reducing power consumption while maintaining measurement precision for the specific parameter of contact area length.
Solution Approach 2:
The patent changes the parameter of sampling frequency from high (required for direct profile reconstruction) to low (sufficient for statistical estimation). This parameter change enables the system to operate with reduced power consumption while still achieving accurate measurement of contact area length through statistical analysis of the undersampled data.
2Measurement precision
If high sampling frequency is used to properly reconstruct the acceleration profile, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential information needed for contact area length estimation from the tire deformation signal, rather than attempting to fully reconstruct the entire acceleration profile. By using statistical methods to extract contact area parameters directly from low-frequency samples, the system avoids the need for sophisticated hardware required for complete profile reconstruction, thereby reducing device complexity while maintaining measurement precision for the specific parameter of interest.
Solution Approach 2:
The patent replaces the mechanical/system requirement of high-frequency sampling hardware with a statistical processing approach. Instead of relying on complex high-speed sensors and processors to capture and reconstruct every detail of tire deformation, the system uses simple low-frequency sampling combined with statistical analysis to achieve the same measurement objective, thereby reducing device complexity.
3Use of energy by moving object
If low sampling frequency is used to reduce power consumption, then power consumption is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent applies partial action by using low-frequency sampling that is insufficient for direct reconstruction of the deformation profile, but sufficient for statistical estimation of contact area parameters. Instead of continuously sampling at high frequency to capture every detail of tire deformation, the system samples sparsely and uses statistical methods to derive the necessary information, thereby reducing power consumption while maintaining measurement precision for the specific parameter of contact area length.
Solution Approach 2:
The patent changes the parameter of sampling frequency from high (required for direct profile reconstruction) to low (sufficient for statistical estimation). This parameter change enables the system to operate with reduced power consumption while still achieving accurate measurement of contact area length through statistical analysis of the undersampled data.
4Measurement precision
If sophisticated hardware with high sampling frequency is used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential information needed for contact area length estimation from the tire deformation signal, rather than attempting to fully reconstruct the entire acceleration profile. By using statistical methods to extract contact area parameters directly from low-frequency samples, the system avoids the need for sophisticated hardware required for complete profile reconstruction, thereby reducing device complexity while maintaining measurement precision for the specific parameter of interest.
Solution Approach 2:
The patent replaces the mechanical/system requirement of high-frequency sampling hardware with a statistical processing approach. Instead of relying on complex high-speed sensors and processors to capture and reconstruct every detail of tire deformation, the system uses simple low-frequency sampling combined with statistical analysis to achieve the same measurement objective, thereby reducing device complexity.
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 method enables precise estimation of tire contact area length and related parameters like load, using statistical analysis of undersampled data, reducing hardware complexity and power consumption while maintaining accurate monitoring.
Implementation Method 1
The electronic unit comprises at least one sensor (for example a temperature sensor, a pressure sensor, a sensor able to measure/identify the tire's deformations during rolling, such as, for example, an accelerometer, a strain gauge, a piezoelectric sensor etc.)
Data Source
AI summary
A monitoring of a tire is performed by using a monitoring unit operated at low frequency and with low power needs, without the need of providing complex hardware and software adapted for reconstructing a signal descriptive of the tire deformations and/or for recognizing the start and the end of peaks or valleys or other significant points of such signal. The monitoring uses a statistical approach for the estimation of the length of the contact area, or of other parameters related to it, based on an estimation of a probability of finding the monitoring unit in correspondence of the contact area at a certain time during rolling.