Tire Vertical Load Prediction Using Thermal Behavior Modeling
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Solution Overview
Problem
Current tire wear prediction systems lack accurate and reliable measurement of vertical load, a critical factor in tire wear assessment, due to the expense and unreliability of conventional sensors.
Innovation Solution
A computer-implemented method and system that predicts vertical load using typical sensor measurements like vehicle speed, ambient temperature, and tire inflation pressure, by storing thermal characteristics and generating a model to determine transient temperature behavior, allowing for reliable tire wear prediction and maintenance alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sensors are used to measure vertical load, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces mechanical load sensors with a thermal-based prediction system. By measuring tire temperature (which is easier and cheaper to obtain) and using thermal models to infer vertical load, the system substitutes a complex mechanical measurement system with a simpler thermal field-based approach. This resolves the contradiction by maintaining measurement capability while reducing device complexity.
Solution Approach 2:
The patent introduces temperature as an intermediary parameter between vertical load and measurable quantities. Instead of directly measuring vertical load, the system measures temperature (which responds to load) and uses thermal characteristics as a mediator to predict load. This intermediary approach enables indirect measurement without requiring complex direct load sensors.
2Measurement precision
If conventional sensors are used to measure vertical load, then measurement precision is improved, but reliability deteriorates
Solution Approach 1:
The patent replaces unreliable mechanical load sensors with a thermal measurement and prediction system. Temperature sensors are more reliable and less prone to failure than load cells, and the thermal model provides a robust method for inferring load. This substitution improves reliability while maintaining the ability to obtain vertical load information.
3Device complexity
If thermal characteristics and modeling are used to predict vertical load, then device complexity is reduced, but measurement precision may deteriorate
Solution Approach 1:
The patent performs preliminary characterization of tire thermal characteristics under various known load conditions. By pre-establishing the relationship between temperature and vertical load through experimentation or simulation, the system creates a lookup table or model that can be used for prediction. This preliminary action enables accurate predictions without requiring complex real-time calculations, resolving the contradiction between simplicity and precision.
Solution Approach 2:
The system uses measured temperature feedback combined with thermal models to continuously predict vertical load. The temperature measurements provide ongoing feedback about tire conditions, which are processed through the thermal model to update load predictions. This feedback mechanism maintains prediction accuracy while keeping the system simple and adaptable to changing 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
Enables accurate and reliable prediction of vertical load, improving tire wear assessment and enabling timely maintenance alerts, thereby enhancing safety and reducing unnecessary tire replacements.
Implementation Method 1
predicting transient temperature behavior based on one or more tire-specific time constants
Data Source
AI summary
A computer-implemented method as disclosed enables predicting of vertical loads on a vehicle tire. Thermal characteristics for a particular vehicle-tire combination are retrievably stored, the thermal characteristics determined as corresponding to a range of temperature values further correlated with a plurality of operating conditions, and the plurality of operating conditions comprising at least a vertical load. A model for predicting transient temperature behavior is generated (e.g., empirically trained) based on one or more tire-specific time constants. During operation of the vehicle-tire combination and responsive to at least a first temperature value, a computing device residing on the vehicle or otherwise cloud-based in nature is configured to determine a predicted vertical load based on a predicted second temperature value from the model and further based on the retrievably stored one or more thermal characteristics.