Tire Wear Estimation via Wheel Acceleration Mode Extraction
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Solution Overview
Problem
Existing tire wear monitoring systems face challenges such as sensor damage during tire curing, durability issues, cost, and accuracy problems due to reliance on direct tire-mounted sensors and inadequate prediction techniques using non-standard vehicle data.
Innovation Solution
A tire wear state estimation system utilizing a CAN bus system and processor to analyze longitudinal and vertical acceleration signals from a wheel sensor unit, extracting tire translational and vertical modes, and employing a classifier for accurate wear state estimation without direct tire pressure input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wear sensors are disposed in the tire tread (direct method), then tire wear state can be directly measured, but sensor damage during curing, durability issues, and high cost occur
Solution Approach 1:
The patent uses wheel acceleration signals as an intermediary to indirectly estimate tire wear state. Instead of placing sensors directly in the tire tread, the system measures wheel acceleration through existing wheel speed sensors and processing systems, then extracts wear information from these intermediary measurements through signal processing and classification algorithms.
Solution Approach 2:
The patent replaces the mechanical wear measurement system (physical sensors in tire tread) with a signal processing system. By substituting direct mechanical contact sensors with electronic acceleration signal analysis, the system avoids sensor damage while maintaining wear state estimation capability.
2Measurement precision
If wear sensors are disposed in the tire tread, then tire wear state can be directly measured, but sensor cost and manufacturing complexity increase significantly
Solution Approach 1:
The system uses wheel acceleration signals as an intermediary measurement approach, eliminating the need for complex tire integration of wear sensors. By measuring wheel acceleration through existing vehicle systems and processing the signals computationally, the patent simplifies both tire manufacturing and sensor installation while maintaining measurement capability.
Solution Approach 2:
The patent extracts wear state information from wheel acceleration signals without requiring physical sensors embedded in the tire. By taking out the measurement function from the tire structure itself and placing it in the vehicle's existing sensor and processing system, the complexity of tire manufacturing and sensor integration is eliminated.
3Device complexity
If indirect estimation techniques are used to predict tread wear, then sensor cost and complexity are reduced, but prediction accuracy decreases due to lack of optimum prediction techniques
Solution Approach 1:
The patent employs dynamic classification algorithms that adapt to different driving conditions and tire wear states. By using dynamic programming and classification techniques that process wheel acceleration signals in real-time, the system achieves accurate wear state estimation without requiring complex sensor systems, thereby resolving the accuracy-complexity tradeoff.
Solution Approach 2:
The patent transforms the measurement approach by changing from direct physical wear measurement to indirect acceleration-based estimation. By altering the measurement parameters from direct tread depth to wheel acceleration characteristics, and applying sophisticated signal processing and classification, the system achieves high accuracy with simpler sensor requirements.
4Device complexity
If non-standard vehicle system signals are used for wear prediction, then sensor cost is reduced, but measurement accuracy decreases due to data inaccuracy under all driving conditions
Solution Approach 1:
The patent uses wheel acceleration signals that are universally available across different driving conditions and vehicle types. By leveraging the existing wheel speed sensor and processing systems that already provide acceleration data for various vehicle functions, the system achieves accurate wear estimation without requiring additional specialized sensors, ensuring data availability and accuracy under all operating 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
The system provides accurate and reliable tire wear state estimation using easily obtained and accurate parameters, avoiding the limitations of direct sensor measurements and improving prediction accuracy without additional sensors or high costs.
Implementation Method 1
a longitudinal acceleration sensor to measure a longitudinal acceleration of the wheel and generate a longitudinal acceleration signal
Implementation Method 2
a vertical acceleration sensor to measure a vertical acceleration of the wheel and generate a vertical acceleration signal
Data Source
AI summary
A tire wear state estimation system includes a CAN bus system disposed on a vehicle. A tire supporting the vehicle is mounted on a wheel. A wheel sensor unit is mounted on a structure adjacent the wheel, and the wheel sensor unit includes a longitudinal acceleration sensor to generate a longitudinal acceleration signal. The wheel sensor unit also includes a vertical acceleration sensor to generate a vertical acceleration signal, and transmission means to communicate the longitudinal acceleration signal and the vertical acceleration signal to the CAN bus system. A processor receives the longitudinal acceleration signal and the vertical acceleration signal. An extractor extracts a tire translational mode from the longitudinal acceleration signal and a tire vertical mode from the vertical acceleration signal. The tire translational mode and the tire vertical mode are input into a classifier to generate a wear state estimation for the tire. A method is also provided.