Tire Pressure Control via Acoustic Wave Detection and Adaptive Recalibration
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Solution Overview
Problem
Existing tire pressure control systems are inefficient in adapting to dynamic vehicle conditions and require costly and bulky components for accurate pressure control, lacking self-optimization and real-time adaptation to changes in the air supply and tire dynamics.
Innovation Solution
A microcontroller-based system that learns and optimizes tire pressure control algorithms in real-time, using air pressure sensors and valves to autonomously adjust pressure without operator intervention, and recalibrates based on operational data to ensure accurate and efficient pressure changes, while detecting potential system failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional tire pressure control systems use sensors and control mechanisms, then tire pressure can be monitored and adjusted, but the system becomes costly and bulky
Solution Approach 1:
The patent replaces traditional mechanical pressure sensors with acoustic wave-based detection. By analyzing acoustic emissions from the tire valve stem, the system determines pressure levels without requiring bulky or expensive sensor hardware. This substitution of mechanical measurement with acoustic field analysis resolves the contradiction between measurement precision and device complexity.
Solution Approach 2:
The patent introduces acoustic waves as an intermediary medium to transfer pressure information from the tire interior to the detection device. Instead of directly measuring pressure with sensors inside the tire, the system uses acoustic emissions that carry pressure data through the valve stem, enabling indirect but accurate measurement with simpler components.
2Adaptability or versatility
If tire pressure control systems use fixed control algorithms, then implementation is simple, but the system cannot adapt to dynamic vehicle conditions
Solution Approach 1:
The patent implements dynamic control algorithms that continuously adapt to changing vehicle conditions such as speed, load, and road surface. The system adjusts tire pressure in real-time based on detected acoustic signals and environmental factors, transforming a static control system into a dynamic one that responds to operational conditions, thereby achieving adaptability without excessive complexity.
Solution Approach 2:
The system incorporates feedback mechanisms where acoustic emissions from the tire valve are continuously monitored and fed back to the control algorithm. This feedback loop enables the system to learn from operational data and adjust control parameters dynamically, achieving adaptability to changing conditions while maintaining manageable system complexity through iterative optimization.
3Reliability
If tire pressure adjustment is performed frequently, then optimal pressure is maintained, but valve operational cycles increase causing wear
Solution Approach 1:
The patent applies partial action by adjusting tire pressure only when necessary, based on real-time acoustic monitoring and predicted optimal pressure requirements. Instead of frequent adjustments, the system performs targeted pressure changes only when deviations from optimal pressure are detected or anticipated, reducing valve operational cycles while maintaining reliable tire pressure through precise, condition-based intervention.
Data Source
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AI summary
A tire pressure control system for a vehicle has a supply of compressed air connected to a vehicle tire through an air conduit having a valve and an air pressure sensor that senses the air pressure in the vehicle tire. A microcontroller is connected to control the valve to supply compressed air to the vehicle tire or to vent compressed air from the vehicle tire. The microcontroller has instructions to: calculate a valve operation required to achieve a target pressure; operate the valve according to the calculated valve operation; measure an adjusted air pressure after the calculated valve operation is completed; calculate a further valve operation to achieve the target pressure if necessary; and compare the results of the valve operation to the calculated valve operation and recalibrating the algorithm based on any differences.