Tire Pressure Sensor Auto-Learn via Motion and Burst Analysis
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Solution Overview
Problem
Existing tire pressure monitoring systems face challenges in correctly associating new sensors with their respective tire locations, often leading to customer dissatisfaction and increased warranty claims due to incorrect associations and lengthy identification processes.
Innovation Solution
The system employs an auto-learn function that uses burst mode transmissions and a combination of sensor IDs, burst counters, and motion detection to quickly and accurately associate tire pressure sensors with their corresponding tires, reducing the risk of incorrect associations and speeding up the identification process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing auto learn functions are used to associate sensors with tire locations, then sensor association is performed automatically, but incorrect associations occur and the process takes unduly long periods of time
Solution Approach 1:
The system performs preliminary actions by detecting sensor motion patterns and burst transmission characteristics before final association. The receiver monitors sensor behavior during vehicle operation, collects data about sensor locations through multiple transmissions, and pre-associates sensors with tire locations before completing the full learn process, thereby reducing both time and errors
Solution Approach 2:
The system uses feedback mechanisms where the receiver continuously monitors sensor transmissions and adjusts associations based on observed patterns. By analyzing burst counter values, motion detection data, and transmission timing, the system refines sensor-location mappings iteratively, improving association accuracy while maintaining automation
2Extent of automation
If existing auto learn functions are used to associate sensors with tire locations, then sensor association is performed automatically, but the process requires unduly long periods of time
Solution Approach 1:
The system skips unnecessary waiting periods by actively monitoring sensor transmissions during normal vehicle operation rather than requiring dedicated learn time. By processing sensor data in real-time during regular driving, the system rushes through the association process without unduly delaying sensor functionality
Solution Approach 2:
The receiver performs preliminary association based on initial sensor detections and motion patterns, establishing provisional sensor-location mappings before complete data collection. This preliminary action reduces the total time required by not waiting for all sensor data to be collected before making associations
3Adaptability or versatility
If new sensors are installed in the sensor system, then the system can monitor additional tires, but the sensors need to be properly associated with the receiver to avoid fault flags
Solution Approach 1:
The system enables self-service by allowing newly installed sensors to automatically associate with the receiver through motion detection and burst transmission analysis. The receiver autonomously identifies new sensors, determines their locations, and completes association without requiring manual configuration or complex user procedures
Solution Approach 2:
The system performs preliminary association actions during sensor installation by detecting motion patterns and transmission characteristics. The receiver prepares association data in advance based on observed sensor behavior, making the overall process easier and reducing the likelihood of association errors
Data Source
AI summary
Frames of data are received. Each frame includes at least a sensor identifier and a changeable data field and is sent from one of a plurality of sensors. Each of the plurality of sensors is associated with a respective one of a plurality of sensor identifiers. The changeable data field includes, in some of the frames, data representing a sensed condition and, in others of the frames, counter data. The counter data is analyzed to determine whether any of the sensor identifiers can be associated with one of a plurality of sensor locations.