Tire Acceleration Volatility for Aquaplaning Detection
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Solution Overview
Problem
Existing tire monitoring systems require acquiring and storing reference curves for normal tire behavior, which becomes inaccurate over the tire's lifetime due to changes in mechanical properties and tread depth, leading to inefficient aquaplaning detection.
Innovation Solution
A method that acquires a signal representative of a tire's acceleration, derives a curve representing the acceleration profile, determines leading and trailing portions, calculates volatility measures based on RMS noise, and calculates a difference between these measures to indicate tire behavior without relying on reference curves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reference curves are acquired and stored for normal tire behavior, then tire monitoring can be performed, but the reference curves become inaccurate over the tire's lifetime due to changes in mechanical properties and tread depth
Solution Approach 1:
The system uses the tire's own operational data to continuously update and refine the reference curve, allowing the monitoring system to adapt to the tire's changing characteristics over time without external intervention. The evaluation unit automatically adjusts the reference curve based on actual measured values during tire operation.
Solution Approach 2:
The reference curve is transformed from a static parameter to a dynamic parameter that changes over time. The system continuously updates the reference curve parameters based on actual tire performance data, ensuring the reference remains accurate throughout the tire's lifetime despite changes in mechanical properties and tread depth.
2Measurement precision
If reference curves are continuously updated to maintain accuracy, then monitoring precision improves, but system complexity and computational requirements increase
Solution Approach 1:
The system updates the reference curve selectively rather than continuously, using partial updates based on significant changes in tire behavior or at predetermined intervals. This approach maintains measurement precision while reducing the computational burden and system complexity associated with constant updates.
3Reliability
If traditional aquaplaning detection methods are used, then detection capability is provided, but the system requires predetermined reference signals that become obsolete over time
Solution Approach 1:
The system implements a feedback mechanism where actual tire measurement data is continuously fed back to update the reference curve. This closed-loop approach ensures the reference signal remains current and accurate by incorporating real-world tire performance information, preventing the reference from becoming obsolete.
Data Source
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AI summary
The invention relates to a method for monitoring a behavior of a tire (2) of a vehicle (1) in a rolling condition of the tire, comprising the steps of: a) acquiring (S1) a signal (a) representative of an acceleration of a specified point of the tire (2), b) deriving (S2) from the signal (a) a curve which represents a profile of the acceleration of the point during a revolution of the tire (2), c) determining (S3) a leading portion and a trailing portion of the curve, corresponding to an entry of the point into a footprint region of the tire (2) and corresponding to an exit of the point from the footprint region of the tire (2), respectively, d) determining (S4) a first measure of a volatility of the signal (a) in the leading portion and a second measure of a volatility of the signal (a) in the trailing portion, and e) determining (S5) an indication of the behavior of the tire (2) based on the first measure and the second measure. In particular, the method may be used e.g. for aquaplaning warning or e.g. for detection of an offroad condition.