Tire Pressure Detection Using Bayesian Resonance Frequency Estimation
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Solution Overview
Problem
Existing tire pressure monitoring systems using the Resonance Frequency Method face challenges in accurately detecting decreased tire pressure due to small pressure decrease sensitivity and highly-dispersed resonance frequencies among default tires, leading to false alarms and inadequate detection under various conditions.
Innovation Solution
An apparatus and method employing Bayesian estimation based on stored distribution information of resonance frequencies for tires at different air pressure statuses, using rotation speed and acceleration data to accurately determine tire pressure status, even with diverse tire properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the Resonance Frequency Method is used to detect tire pressure, then the system can detect four wheels simultaneous deflation and provide absolute comparison with normal values, but the estimated frequency value becomes not robust against vehicle speed and road surface situation
Solution Approach 1:
The patent introduces an intermediary variable (resonance frequency extraction from wheel speed signals) that mediates between the wheel speed sensor data and the tire pressure detection. By using the resonance frequency as an intermediate characteristic that is less sensitive to vehicle speed and road surface conditions, the system achieves more robust tire pressure monitoring while maintaining the ability to detect four-wheel simultaneous deflation.
Solution Approach 2:
The patent changes the detection parameter from direct wheel speed comparison to resonance frequency analysis. By transforming the detection approach to focus on frequency domain characteristics rather than time domain speed values, the system achieves better robustness against varying vehicle speed and road surface conditions while maintaining detection reliability.
2Device complexity
If conventional frequency estimation methods are used, then the computation is relatively simple, but the frequency estimation becomes inaccurate under various running conditions due to noise and dispersion
Solution Approach 1:
The patent applies preliminary action by pre-storing the distribution characteristics (mean and standard deviation) of resonance frequencies under normal tire pressure conditions. This pre-acquired statistical information is then used to guide the frequency estimation process, improving accuracy without requiring complex real-time computations. The system prepares reference data in advance to facilitate more accurate detection during actual operation.
Solution Approach 2:
The patent implements feedback by using the stored distribution information of resonance frequencies to continuously refine and correct the frequency estimation process. The system compares estimated frequencies against the pre-stored distribution characteristics and adjusts its detection threshold and estimation algorithm accordingly, creating a closed-loop system that improves accuracy while maintaining computational efficiency.
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
The method effectively determines decreased tire pressure with high accuracy, reducing false alarms and improving detection reliability across different tire types and conditions.
Implementation Method 1
When the vehicle is running, the tires receive a force from the road surface to thereby cause the torsional motion in the front-and-rear direction and the front-and-rear motion of the suspension, and these motions have a coupled resonance vibration.
Implementation Method 2
the tires receive a force from the road surface to thereby cause the torsional motion in the front-and-rear direction
Data Source
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AI summary
An apparatus for detecting a tire having a decreased pressure based on resonance frequency of tires attached to respective wheels of a vehicle. The apparatus includes a storage means for storing information regarding a distribution of resonance frequencies respectively corresponding to a plurality of air pressure statuses, an initialization means for estimating a frequency characteristic of the rotation speed information or the rotation acceleration information, a frequency estimation means for estimating a frequency characteristic of the rotation speed information or the rotation acceleration information of a running vehicle, and a Bayesian estimation means for subjecting a tire pressure status at a certain time to a Bayesian estimation based on the resonance frequency during the initialization, a resonance frequency at the certain time obtained from the frequency estimation means, and distribution-related information stored in the storage means.