Tire Classification via Wheel Speed and CAN Bus Data
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Solution Overview
Problem
Current vehicle control systems and driver information systems lack an accurate and efficient method for determining tire class, which affects the performance of systems like TCS, ESP, and ABS, relying on limited input parameters such as slip ratios and rotational information.
Innovation Solution
The method utilizes sensor signals from wheel speed sensors and internal data buses, like FlexRay/CAN, to estimate vehicle properties parameters, such as tire longitudinal stiffness and temperature, to determine tire class using predetermined relations and decision boundaries, enabling classification into types like summer, winter, or all-season tires.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional tire classification methods using limited input parameters (slip ratios, rotational information) are used, then the system complexity remains low, but the measurement precision and reliability of tire class determination deteriorates
Solution Approach 1:
The patent reuses existing sensors (wheel speed sensors, acceleration sensors) and data infrastructure (CAN bus, FlexRay) from standard vehicle equipment for multiple purposes - originally designed for ABS/traction control, now also used for tire classification. This eliminates the need for dedicated tire classification hardware while achieving accurate tire type identification through multi-parameter analysis of available sensor data.
2Measurement precision
If comprehensive vehicle properties parameters are estimated and analyzed, then the tire class determination accuracy improves, but the loss of time for processing increases
Solution Approach 1:
The system continuously estimates vehicle properties parameters (tire longitudinal stiffness, temperature, pressure, wear) in real-time using pre-established physical models and sensor data fusion algorithms. By maintaining continuous estimation rather than periodic batch processing, the system has tire classification data ready immediately when needed, eliminating processing delays while maintaining high accuracy through ongoing multi-parameter analysis.
3Ease of manufacture
If existing sensor data from ABS systems is reused for tire classification, then the ease of manufacture and cost reduce, but the quantity of useful information for tire classification is insufficient
Solution Approach 1:
The patent segments the available sensor data into multiple independent vehicle properties parameters (tire longitudinal stiffness, temperature, pressure, wear indicators) by applying different physical models and analysis methods to the same raw sensor signals. This segmentation transforms limited raw data into multiple useful classification features, increasing the effective data quantity without requiring additional sensors or system complexity.
Data Source
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AI summary
A system and a method of determining a tire class of a tire mounted on a wheel of a driving vehicle based on at least one sensor signal received from a sensors comprised in the vehicle.