Tire Longitudinal Stiffness Estimation Using Real-Time Mu-Slip Curves
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Solution Overview
Problem
Existing tire monitoring systems require complex data from multiple sources and significant computing power, making real-time longitudinal stiffness estimation challenging and resource-intensive, often necessitating cloud computing and prolonged processing times.
Innovation Solution
A system comprising a vehicle-mounted electronic communication system, sensors, a processor, a mu slip curve generator, an extraction module, and a denoising module that calculates longitudinal stiffness using limited data sources, applying principal component analysis and Kalman filters to generate accurate real-time estimates with low computing load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex systems employing data from multiple sources are used to generate accurate longitudinal stiffness estimates, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts and utilizes only the essential parameters needed for stiffness estimation from the vehicle system, specifically selecting wheel acceleration, wheel speed, and vehicle longitudinal acceleration. This extraction approach maintains estimation accuracy while eliminating the need for complex multi-source data integration systems.
Solution Approach 2:
The patent creates a virtual mu-slip curve through computational modeling rather than requiring physical sensors or complex measurement systems. By generating a simulated curve based on processed acceleration data, the system achieves accurate stiffness estimation without the complexity of multiple physical data sources.
2Measurement precision
If complex systems with multiple data sources are used for stiffness estimation, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system extracts only the necessary acceleration and speed parameters that are already available in most vehicle systems, eliminating the need for additional complex sensor installations or data collection infrastructure, thereby simplifying implementation.
Solution Approach 2:
The system utilizes data that is already being collected by the vehicle's existing sensors and control systems. By processing readily available wheel acceleration, wheel speed, and longitudinal acceleration data, the system avoids the operational complexity of integrating multiple external data sources.
3Measurement precision
If systems with significant computing load are used for real-time stiffness estimation, then measurement precision is improved, but productivity deteriorates
Solution Approach 1:
The patent replaces complex computational algorithms with a streamlined processing approach that uses basic mathematical operations on acceleration and speed data. By substituting heavy computational methods with efficient signal processing techniques, the system achieves real-time performance on vehicle-mounted processors.
Solution Approach 2:
The system transforms the estimation problem by changing the computational parameters from complex multi-source data integration to simple processing of acceleration and speed derivatives. This parameter transformation enables real-time calculation while maintaining estimation accuracy.
4Measurement precision
If systems requiring cloud computing resources are used for stiffness estimation, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent performs all necessary computational processing locally on the vehicle-mounted processor using readily available sensor data. By completing the estimation calculation immediately with pre-positioned algorithms and local computing resources, the system eliminates time delays associated with cloud communication and remote processing.
Solution Approach 2:
The system uses the vehicle's existing electronic communication system and processor as intermediaries to perform real-time estimation locally. This eliminates the need for external cloud computing intermediaries, thereby reducing latency and enabling immediate stiffness estimation for control system integration.
Data Source
AI summary
A tire longitudinal stiffness estimation system includes an electronic communication system disposed on a vehicle. A sensor is disposed on the vehicle in communication with the electronic communication system, and a processor is accessible through the electronic communication system. The sensor measures parameters associated with the vehicle and communicates data for the parameters to the processor. A mu slip curve generator receives the parameters to generate a mu slip curve in real time from the data. An extraction module extracts raw data from a linear portion of the mu slip curve. A denoising module de-noises the raw data from the mu slip curve by determining a vector for the raw data, an orientation of the vector, and a heading of the vector. The denoising module generates de-noised data, and a stiffness calculator receives the de-noised data and generates a longitudinal stiffness estimate for the tire.