Tire Wear Detection Using Normalized Rolling Radius
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Solution Overview
Problem
Existing methods for determining tire wear, such as visual inspection and manual measurement, are difficult to implement and require improvements in real-time monitoring, which can cause tires to burst during vehicle operation.
Innovation Solution
A method and device for automatically determining tire wear using sensors and machine learning models to assess tire wear in real-time, providing notifications and adapting vehicle systems for optimal performance and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visual inspection and manual measurement are used to determine tire wear, then the method is simple to implement, but the detection timeliness is poor and may lead to tire failure
Solution Approach 1:
The patent replaces manual visual inspection and mechanical measurement with an automated sensor-based system. Sensors mounted on the vehicle continuously collect data about tire conditions, and a processing system automatically analyzes this data to determine wear levels, eliminating the need for manual intervention and enabling real-time monitoring.
Solution Approach 2:
The system implements continuous monitoring of tire wear through ongoing data collection from sensors during vehicle operation. Rather than periodic manual checks, the system continuously tracks tire parameters and automatically updates wear assessments, ensuring timely detection without interrupting vehicle use.
2Productivity
If automated sensor-based real-time tire wear determination is implemented, then detection timeliness and reliability are improved, but the device complexity increases
Solution Approach 1:
The system uses multi-functional sensors that collect various types of data (vibration, temperature, pressure, acceleration) to assess multiple tire parameters simultaneously. This universal approach allows a single sensor suite to perform comprehensive tire monitoring, reducing the need for multiple specialized devices and minimizing overall system complexity.
Solution Approach 2:
The system automatically processes sensor data and generates wear assessments without requiring manual intervention. The processing system self-manages data collection, analysis, and interpretation, converting raw sensor signals into actionable wear information autonomously, which simplifies operation despite the underlying technical complexity.
3Measurement precision
If machine learning models are used to calculate normalized rolling radius and stiffness, then measurement precision is improved, but the computational requirements and processing time increase
Solution Approach 1:
The system pre-processes sensor data during collection to extract relevant features before feeding them to machine learning models. By preparing and filtering data in advance, the system reduces the computational burden during actual wear assessment, lowering energy consumption while maintaining measurement precision through thoughtful data preparation.
Data Source
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AI summary
A method of determining a wear of a tire, which may include, using a computing device operating a processor: based on signals from one or more sensors of a vehicle, determining a plurality of tire parameters of a tire; based on at least a portion of the tire parameters, determining a normalized rolling radius of the tire, the normalized rolling radius being an effective rolling radius of the tire under a zero rotational speed, a zero load or both; and based on a change in the normalized rolling radius of the tire over a period of time, determining an average wear value of the tire.