TPMS Sensor Localization via Signal Strength and Bayesian Classification
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Solution Overview
Problem
Current tire pressure monitoring systems (TPMS) face challenges in providing real-time or near real-time tire pressure values and accurate localization of TPMS sensors, especially when tires are rotated or changed, leading to potential delays and incorrect wheel identification, which can result in unsafe driving conditions due to outdated pressure measurements and increased complexity with multiple antennas.
Innovation Solution
A system utilizing a limited number of antennas, such as one or two, to determine signal strength values between TPMS sensors and an antenna, allowing for the localization of each sensor based on signal strength, angle of arrival, or time of flight, with a processor configured to average multiple measurements and use stochastic models or Bayesian classifiers for accurate positioning, even when tires rotate or change positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple antennas are used to determine TPMS sensor locations, then localization accuracy is improved, but device complexity increases
Solution Approach 1:
The patent divides the localization function into two parts: a limited number of antennas (one or two) perform signal strength measurements, while a processor performs the complex computation using stochastic models and Bayesian classifiers to determine sensor locations. This segmentation allows accurate localization without requiring multiple physical antennas at every position.
Solution Approach 2:
The patent replaces a mechanical/array-based multi-antenna system with a computational approach using stochastic models and Bayesian classifiers. Instead of using multiple physical antennas to geometrically determine position, the system uses signal strength measurements processed through probabilistic algorithms to infer sensor locations, reducing hardware complexity while maintaining accuracy.
2Use of energy by moving object
If TPMS sensors transmit information at a slow rate to conserve battery life, then energy consumption is reduced, but real-time monitoring capability deteriorates
Solution Approach 1:
The system continuously receives signal strength measurements from TPMS sensors and uses Bayesian classifiers to update sensor location probabilities in real-time. This feedback mechanism allows the system to maintain accurate localization knowledge without requiring continuous high-rate data transmission from sensors, as the processor can infer position changes from incremental signal strength updates.
Solution Approach 2:
The patent pre-computes probability distributions and stochastic models for sensor locations based on expected signal strength patterns. When sensors transmit at low rates, the system can interpolate between measurements using these pre-established models, maintaining real-time localization capability without requiring frequent sensor transmissions that would drain battery life.
3Ease of manufacture
If tires are rotated or changed, then tire maintenance is improved, but sensor-location correspondence is lost
Solution Approach 1:
The patent changes the parameter used for identification from fixed positional assignment to dynamic signal strength-based probability distributions. When tires are rotated or changed, the system recalculates sensor locations using Bayesian classifiers that incorporate current signal strength measurements, automatically adapting to new configurations without requiring manual reconfiguration or losing tracking information.
Solution Approach 2:
The system automatically re-localizes sensors after tire rotation or replacement by using the same signal strength measurement and Bayesian classification process. The processor independently determines new sensor positions based on current antenna measurements and pre-computed probability models, without requiring external intervention or losing the ability to track sensor locations.
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 real-time or near real-time tire pressure monitoring and accurate localization of TPMS sensors without requiring vehicle motion, reducing complexity and cost by using fewer antennas, ensuring driver safety and correct wheel identification.
Implementation Method 1
A processor of the vehicle may be configured for determining signal strength values between each of the plurality of TPMS sensors and an antenna of the vehicle
Implementation Method 2
allowing for the localization of each sensor based on signal strength, angle of arrival, or time of flight
Data Source
AI summary
Method and apparatus are disclosed for localizing vehicle TPMS sensors. An example vehicle includes a plurality of TPMS sensors, an antenna, and a processor. The processor is configured for determining signal strength values between each of the plurality of TPMS sensors and the antenna, and based on the signal strength values, determining a location of each of the plurality of TPMS sensors.