Tire Sensor Position Detection Using RSSI Classifier Relearning
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Solution Overview
Problem
Existing systems struggle to automatically detect and adapt to changes in tire configurations on commercial vehicles due to varying tire positions, signal interference, and lack of ABS sensors, making manual reconfiguration necessary.
Innovation Solution
A method and device that utilize a classifier trained on initial tire configuration and signal strengths to detect changes in tire positions, adjusting the configuration automatically and retraining the classifier as needed, using maximum RSSI values or predefined tire orientations to stabilize signal strength measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual configuration is used to assign tire sensors to wheel positions, then configuration accuracy is ensured, but additional manual effort and time are required when tire positions change
Solution Approach 1:
The system enables automatic self-identification of tire sensor positions through signal strength evaluation. The control unit automatically determines which sensor is at which wheel position based on received signal strengths, eliminating the need for manual reconfiguration when tires are moved or replaced.
Solution Approach 2:
The system performs preliminary teaching during an initial phase where the vehicle is driven with tires in known positions. This teaching phase stores reference signal strength values that are later used for automatic position determination, preparing the system in advance for automatic operation.
2Extent of automation
If automatic detection of tire position changes is implemented, then manual effort is reduced, but signal strength variations due to tire rotation and distance changes cause detection inaccuracies
Solution Approach 1:
The system continuously monitors signal strengths from tire sensors and compares them against reference values stored during the teaching phase. This feedback mechanism allows the control unit to detect when a tire position has changed by identifying deviations from the stored reference pattern.
Solution Approach 2:
The system evaluates signal strength parameters to determine tire positions. By monitoring changes in signal strength characteristics and comparing them against reference patterns, the system can distinguish between normal signal variations and actual position changes.
3Reliability
If multiple receivers are used to improve signal reception, then coverage is enhanced, but system complexity and cost increase
Solution Approach 1:
The control unit performs multiple functions: it manages tire pressure monitoring, stores reference signal strengths during teaching, evaluates current signal strengths, and determines tire positions. This multi-functionality eliminates the need for separate dedicated receivers, reducing system complexity while maintaining reliability.
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
Reduces manual effort by automatically adapting tire configurations and maintaining accurate tire position detection without requiring manual intervention.
Implementation Method 1
receiving signal strengths of radio signals from the electronic components
Data Source
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AI summary
The present invention relates to a method, a computer program with instructions, and a device for operating a control system for electronic components arranged in the tires of a motor vehicle. The invention also relates to a classifier for use in a control system for electronic components arranged in a tire of a motor vehicle, as well as an electronic component for use in a tire of a motor vehicle. In a first step, an initial tire configuration is received (10). Subsequently, during driving operation of the motor vehicle, signal strengths of radio signals from the electronic components are received (11). Based on the initial tire configuration and the signal strengths of the received radio signals, at least one classifier is then trained for at least one tire position (12).After the initial learning (12), the classifier is applied to the signal strength of the received radio signals during driving (13) to detect a change in the tire configuration (14). In response to the detection (14) of a change in the tire configuration, an adjustment (15) of the tire configuration is made and at least one classifier is relearned (12).