Tire Pressure Monitoring with Load-Dependent Warning Thresholds
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Solution Overview
Problem
Existing tire pressure monitoring systems face challenges in adapting to varying vehicle loads without requiring repeated software updates and type approvals, as mandated by regulations like UN ECE-R141, which complicates adjustments to optimal tire pressure for different load conditions.
Innovation Solution
A method that utilizes a load-dependent tire pressure characteristic curve or table, stored in the control unit, to determine optimal tire pressure based on axle load, allowing the system to adjust warnings accordingly, while maintaining compliance with regulatory standards by using temperature compensation and integrating tire pressure data with load sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the tire pressure monitoring system uses a fixed reference pressure for warning detection, then the system complies with regulatory standards (UN ECE-R141), but the system cannot adapt to varying vehicle loads, leading to false warnings or missed detections
Solution Approach 1:
The patent applies the dynamics principle by transitioning from a static fixed reference pressure to a dynamic reference pressure that automatically adjusts based on detected vehicle load conditions. The control unit modifies the reference pressure value in real-time according to load-dependent characteristic curves, enabling the system to adapt to varying loads while maintaining reliable operation within regulatory frameworks.
Solution Approach 2:
The patent implements parameter changes by modifying the reference pressure parameter based on vehicle load conditions. The control unit detects load changes and相应地 adjusts the reference pressure parameter using load-dependent characteristic curves, allowing the system to optimize tire pressure monitoring for different loading scenarios without violating regulatory requirements.
2Reliability
If the system adjusts tire pressure warnings to account for different vehicle loads, then false warnings are reduced, but the system complexity increases due to additional algorithms and data processing
Solution Approach 1:
The patent applies preliminary action by pre-storing load-dependent tire pressure characteristic curves in the control unit's memory before operation. These curves are prepared in advance for various load conditions, allowing the control unit to quickly retrieve and apply the appropriate reference pressure without performing complex real-time calculations, thus reducing algorithmic complexity while improving detection accuracy.
Solution Approach 2:
The patent replaces complex mechanical or computational pressure adjustment mechanisms with a software-based lookup table approach. Instead of using complex algorithms to calculate optimal reference pressure in real-time, the system uses pre-computed characteristic curves stored in memory, substituting computational complexity with simpler data retrieval and comparison operations.
3Reliability
If the system continuously monitors and adjusts reference pressure based on load, then optimal tire pressure is maintained, but energy consumption increases due to continuous sensing and processing
Solution Approach 1:
The patent implements periodic action by monitoring vehicle load conditions at discrete intervals rather than continuously. The control unit checks for load changes at predefined moments and only adjusts the reference pressure when actual load changes are detected, reducing unnecessary processing and energy consumption while maintaining optimal tire pressure monitoring.
Solution Approach 2:
The system applies self-service by automatically detecting load changes and adjusting reference pressure without requiring continuous external intervention or complex control algorithms. The control unit autonomously monitors load conditions and modifies the reference pressure parameter based on pre-stored characteristic curves, enabling the system to self-optimize tire pressure monitoring while minimizing energy usage.
Data Source
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AI summary
In a method for operating a tire pressure monitoring system in a vehicle, the tire pressure of a vehicle wheel is monitored by a tire sensor module. The tire sensor module has a pressure sensor and a transmitting unit, communicates with a programmable electronic control unit of the vehicle, and periodically transmits a sensor data set containing tire pressure data and data for identifying the tire sensor module to the control unit. An algorithm programmed in the control unit provides for the output of a warning signal via signal output devices in the vehicle if the pressure sensor detects a drop in tire pressure beyond a maximum permissible value. For this purpose, tire pressure values are stored in a memory of the control unit as data of a tire pressure characteristic curve or tire pressure table, which represent the dependence of a tire pressure required based on the tire design on the axle load.During vehicle operation, the current axle load is determined by load sensors, transmitted as data to the control unit, and stored there in a memory. The algorithm uses the tire pressure determined from the load-dependent tire pressure curve or table data, based on the determined axle load, as the initial value for detecting the maximum permissible drop. A warning signal is output if the pressure sensor in a monitored tire detects a drop in the tire pressure determined from the load-dependent tire pressure curve or table beyond the specified maximum permissible value.