Tire Wear Monitoring With Compensated Acceleration Gradient
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Solution Overview
Problem
Existing methods for monitoring tire wear, particularly through acceleration gradient analysis, are influenced by various context-dependent parameters like tire pressure and load, leading to inaccurate interpretations and the need for costly, factory-specific calibration.
Innovation Solution
A method for determining a compensated acceleration gradient that accounts for changes in tire behavior over its life by acquiring and updating compensation factors using on-line data from sensors, including tire pressure, footprint quotient, and vehicle speed, through a learning phase and multi-linear regression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If factory-specific calibration with preliminary tests is performed, then measurement precision of acceleration gradient is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The system performs self-calibration by automatically determining compensation factors through online learning during normal operation. The tire wear monitoring system calibrates itself without requiring external factory tests or manual intervention, eliminating the need for complex preliminary calibration procedures while maintaining measurement precision.
Solution Approach 2:
The system performs preliminary learning and calibration actions during normal operation before actual tire wear monitoring begins. By accumulating data and determining compensation factors during the learning phase, the system prepares itself in advance for accurate wear detection without requiring separate factory calibration steps.
2Measurement precision
If factory-specific calibration with preliminary tests is performed, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary learning and calibration actions during normal operation before actual tire wear monitoring begins. By accumulating data and determining compensation factors during the learning phase, the system prepares itself in advance for accurate wear detection without requiring separate factory calibration steps.
Solution Approach 2:
The system performs self-calibration by automatically determining compensation factors through online learning during normal operation. The tire wear monitoring system calibrates itself without requiring external factory tests or manual intervention, eliminating the need for complex preliminary calibration procedures while maintaining measurement precision.
3Adaptability or versatility
If compensation factors are determined through online learning phase, then adaptability to different tire types and conditions is improved, but device complexity increases
Solution Approach 1:
The system adapts to different tire types and operating conditions by dynamically adjusting compensation factors based on measured parameters such as acceleration gradient, vehicle speed, and road conditions. The learning algorithm modifies these parameters online to optimize wear detection accuracy for each specific tire and operating scenario.
Solution Approach 2:
The system performs self-calibration by automatically determining compensation factors through online learning during normal operation. The tire wear monitoring system calibrates itself without requiring external factory tests or manual intervention, eliminating the need for complex preliminary calibration procedures while maintaining measurement precision.
4Measurement precision
If compensation factors are updated continuously, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system performs periodic learning phases at predetermined intervals rather than continuous updates. This approach maintains measurement precision by regularly refreshing compensation factors while significantly reducing energy consumption compared to continuous learning operations.
Solution Approach 2:
The system performs preliminary learning and calibration actions during normal operation before actual tire wear monitoring begins. By accumulating data and determining compensation factors during the learning phase, the system prepares itself in advance for accurate wear detection without requiring separate factory calibration steps.
Data Source
AI summary
A method for determining a compensated acceleration gradient for a tire of a vehicle including sensors for acquiring signals indicative of variables considered from a group including: the tire pressure of the tire, the footprint quotient and the speed of the vehicle, the compensated acceleration gradient being a function of a raw acceleration gradient, of instantaneous values and of reference values of the variables. The compensated acceleration gradient is a function of compensation factors obtained by a learning phase of acquiring the values for the raw acceleration gradient and of calculating the compensation factors. A tire wear monitoring method and to a motor vehicle for implementing the methods are also disclosed.