Tire Contact Patch Estimation With Low-Frequency Inertial Sensing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing tire monitoring systems face challenges in accurately estimating the length of the contact area between the tire and the rolling surface, requiring sophisticated and power-hungry hardware with high sampling frequencies, which is costly and inefficient.
Innovation Solution
A statistical approach using low-frequency monitoring units, such as tire rotation-triggered units, to analyze the output of inertial sensors like accelerometers for tire deformations, estimating tire parameters like contact area length through statistical analysis of sensor data over multiple tire rotations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high sampling frequency monitoring units are used to accurately estimate contact area length, then measurement precision is improved, but use of energy and device complexity increase
Solution Approach 1:
The patent changes the sampling frequency parameter from high (kHz range) to low (Hz range), and uses statistical processing methods to compensate for the reduced sampling rate. This allows accurate contact area estimation while dramatically reducing power consumption and hardware requirements.
Solution Approach 2:
The patent replaces complex mechanical signal reconstruction systems with statistical analysis methods. Instead of using high-frequency sensors and complex signal processing hardware, the invention uses statistical algorithms to estimate contact area parameters from low-frequency measurements.
2Measurement precision
If high sampling frequency monitoring units are used to accurately estimate contact area length, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical signal reconstruction systems with statistical analysis methods. Instead of using high-frequency sensors and complex signal processing hardware, the invention uses statistical algorithms to estimate contact area parameters from low-frequency measurements.
Solution Approach 2:
The patent uses simple, low-cost accelerometers and basic processing units instead of expensive high-frequency sensing systems. The monitoring unit can be implemented with inexpensive components while achieving the same measurement goals through statistical processing.
3Use of energy by moving object
If low sampling frequency monitoring units are used, then use of energy and device complexity are reduced, but measurement precision deteriorates
Solution Approach 1:
The patent changes the sampling frequency parameter from high (kHz range) to low (Hz range), and uses statistical processing methods to compensate for the reduced sampling rate. This allows accurate contact area estimation while dramatically reducing power consumption and hardware requirements.
Solution Approach 2:
The patent uses statistical feedback from multiple low-frequency measurements to converge on accurate contact area estimates. By accumulating and analyzing multiple samples over time, the system compensates for the low sampling rate and achieves precision comparable to high-frequency systems.
4Device complexity
If statistical analysis of low-frequency sensor data is used to estimate tire parameters, then use of energy and device complexity are reduced, but measurement precision may deteriorate
Solution Approach 1:
The patent uses statistical feedback from multiple low-frequency measurements to converge on accurate contact area estimates. By accumulating and analyzing multiple samples over time, the system compensates for the low sampling rate and achieves precision comparable to high-frequency systems.
Solution Approach 2:
The patent performs preliminary statistical analysis and calibration to establish accurate estimation models before actual measurement. By pre-processing and calibrating the system with known parameters, the accuracy of subsequent low-frequency measurements is significantly improved.
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 and efficient tire monitoring with reduced power consumption and hardware complexity, allowing real-time estimation of tire parameters like contact area and load without the need for complex signal reconstruction.
Implementation Method 1
measuring, with the accelerometer, a radial acceleration of said crown portion during rotation of the tire
Data Source
Figure 1
Figure 2
Figure 3
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.