Tire-Mounted Impact Signal Timing for Low-Power Contact Patch Sensing
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Solution Overview
Problem
Tire-mounted sensors (TMS) face challenges in maintaining high accuracy for data processing while minimizing battery usage due to the power-intensive nature of high-performance data analysis, which is essential for monitoring tire parameters like acceleration, load, and tread wear.
Innovation Solution
A method involving a tire-mounted acceleration sensor that processes impact signals by calculating a dynamic threshold based on running averages of impact peak acceleration values, generating time-related parameters, and transmitting these to an external server, reducing power consumption and data storage needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-performance data analysis is performed at the sensor to maintain high accuracy in evaluating tire features, then measurement precision is improved, but use of energy increases and drains the battery
Solution Approach 1:
The patent segments the data processing task into two parts: simple real-time processing at the sensor (calculating impact peak acceleration, comparing to threshold, determining contact patch timing) and more complex analysis at a remote server. This segmentation allows the sensor to maintain measurement precision for critical parameters while consuming less energy by performing only essential calculations locally.
Solution Approach 2:
The patent extracts and transmits only the most critical processed data (impact peak acceleration values and contact patch timing information) to a remote server for further analysis. By taking out only the essential measurements from the sensor and performing detailed analysis remotely, the system maintains high measurement precision while significantly reducing the computational burden and energy consumption at the sensor.
2Measurement precision
If complex mathematical operations are performed at the sensor to process acceleration data, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent divides the processing complexity into two levels: the sensor performs simple operations (detecting impact peaks, comparing acceleration values to a threshold, measuring time intervals) while more complex data analysis is performed at a remote server. This segmentation maintains measurement precision for critical parameters while reducing the processing complexity burden on the sensor hardware.
3Loss of information
If all acceleration data is transmitted to an external server, then loss of information is reduced, but use of energy increases due to data transmission
Solution Approach 1:
The patent extracts and transmits only the most essential processed information (impact peak acceleration values and contact patch timing data) to the external server, rather than transmitting all raw acceleration data. This extraction approach maintains the critical information needed for tire feature analysis while significantly reducing the volume of data transmitted, thereby reducing energy consumption.
Solution Approach 2:
The patent performs preliminary processing at the sensor by calculating impact peak acceleration values and determining contact patch timing before transmission. This preliminary action ensures that the most important information is captured and transmitted in a processed form, reducing the need to transmit large volumes of raw data while maintaining information completeness for subsequent analysis at the server.
Data Source
AI summary
A method for measuring impact signals over a plurality of revolutions of a tire that rolls on a road surface is provided, the impact signals being induced in acceleration data measured by an acceleration sensor mounted in the tire at a contact patch coming into contact with the road surface with each revolution of the tire. The method comprises acquiring the acceleration data over a plurality of revolutions of the tire and processing the acceleration data at the sensor. Processing the acceleration data at the sensor comprises processing the acceleration data to measure acceleration values for each impact signal and calculate an impact peak acceleration value (a_min); calculating a running average of the impact peak acceleration value (a_min) over the plurality of revolutions of the tire; measuring a start time and an end time of each impact signal by comparing acceleration values of the acceleration data to a first or second dynamic threshold, wherein the dynamic threshold is adjusted dependent on the running average of the impact peak acceleration value (a_min); and generating, from the measured start time and end time of each impact signal, a time-related parameter chosen from one or more of: a duration of an impact signal (t_patch), a time period between two consecutive impact signals (t_rev), and a ratio between the duration (t_patch) and the time period (t_rev). The method further comprises transmitting the time-related parameter to an external server.