Wheel Speed FFT Tread Depth Estimation Under Road Disturbance
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Solution Overview
Problem
Existing tire wear monitoring systems face challenges such as impaired sensor operation due to high temperatures, durability issues, cost, and inaccurate indirect estimation methods, particularly in determining tire wear state from wheel speed signals due to manufacturing errors and vibration disturbances.
Innovation Solution
A system that utilizes a processor to process wheel speed signals through a Fast Fourier Transform (FFT) to generate a curve, normalizes it based on tire pressure, vehicle speed, and road roughness, selects a predefined range, fits a reference curve, and employs a regression model to determine tire tread depth using residuals between real-time and reference curves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wear sensors are placed in the tire tread for direct measurement, then measurement precision is improved, but device complexity and cost increase, and sensor durability decreases due to high temperature and mechanical stress
Solution Approach 1:
The patent replaces mechanical wear sensors with a signal processing system that uses wheel speed data and Fast Fourier Transform analysis to estimate tread depth. This substitutes a mechanical sensing system with an electronic computation system that processes existing wheel speed signals to derive wear information without physical contact with the tire tread.
Solution Approach 2:
The patent introduces an intermediary signal processing approach that uses wheel speed signals as a mediator to indirectly measure tread wear. Instead of placing sensors directly in the tire, the system uses wheel speed variations caused by tread wear as an intermediate indicator to estimate remaining tread depth through spectral analysis.
2Device complexity
If indirect estimation methods are used to avoid sensor placement challenges, then device complexity is reduced, but measurement precision decreases due to inaccuracies in resonance frequency extraction from wheel speed signals
Solution Approach 1:
The patent applies preliminary signal processing actions including filtering and normalization of wheel speed signals before performing Fast Fourier Transform analysis. This preprocessing removes noise and standardizes the input data, enabling more accurate extraction of resonance frequencies and improving the precision of tread wear estimation from indirect measurements.
Solution Approach 2:
The system uses feedback through continuous monitoring of wheel speed signals and comparison of spectral characteristics against reference values to refine tread wear estimates. The analysis of residual sums and pattern matching provides feedback mechanisms that improve measurement accuracy over time and across different driving conditions.
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
Accurately and reliably estimates tire tread depth by minimizing interference from tire pressure, speed, and road conditions, providing repeatable and precise tire wear assessment across various tire types.
Implementation Method 1
A Fast Fourier Transform computation module is in electronic communication with the processor, receives the processed wheel speed signals, and generates a Fast Fourier Transform curve
Data Source
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AI summary
A method and system for estimation of a depth of a tread of a tire supporting a vehicle is disclosed. The method comprises: providing a processor in electronic communication with an electronic control system of the vehicle; providing a wheel speed signal processing module in electronic communication with the processor, the wheel speed signal processing module receiving measured wheel speed signals and generating processed wheel speed signals from the measured wheel speed signals; providing a Fast Fourier Transform computation module in electronic communication with the processor, the Fast Fourier Transform computation module receiving the processed wheel speed signals and generating a Fast Fourier Transform curve; providing a summation module in electronic communication with the processor, the summation module selecting a predefined range of the Fast Fourier Transform curve, generating a reference curve from the predefined range of the Fast Fourier Transform curve, and determining a sum of residuals between a real-time Fast Fourier Transform curve and the reference curve; and providing a regression model in electronic communication with the processor, the regression model determining an estimate of tire tread depth from the sum of residuals.