Vehicle Slip Angle Comparison for Surface Friction Changes
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Solution Overview
Problem
Existing systems fail to accurately determine changes in surface friction between different conditions, leading to inappropriate vehicle control, especially in autonomous vehicles that travel pre-defined routes repeatedly.
Innovation Solution
A computer system that compares slip angles from first and second sets of surface conditions to determine differences in friction, using data such as slip angles, lateral acceleration, and other vehicle parameters to adjust control strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If friction estimation models use data from wheel torques and axle loads, then surface friction can be calculated, but the estimation becomes inaccurate when surface conditions change between journeys
Solution Approach 1:
The system uses feedback by comparing slip angles from multiple journeys to detect changes in surface friction. The computer system receives slip angle data from different surface conditions, compares the data, and uses the detected differences to update friction estimates for future vehicle control, creating a closed-loop adaptive system.
Solution Approach 2:
The system performs preliminary action by collecting and analyzing slip angle data from previous journeys before the actual vehicle operation. This advance friction characterization allows the system to pre-adjust control parameters for upcoming trips on similar routes, improving responsiveness to surface condition changes.
2Productivity
If vehicles travel pre-defined routes repeatedly, then operational efficiency is improved, but surface friction changes due to weather and other factors are not detected
Solution Approach 1:
The system implements feedback by continuously monitoring slip angles during repeated route operations and comparing them against baseline data. When deviations are detected indicating surface friction changes, the system adjusts vehicle control parameters accordingly, maintaining reliability while preserving the efficiency benefits of repeated route operations.
Solution Approach 2:
The system applies dynamics by making the friction estimation adaptive rather than static. Instead of using fixed friction values for repeated routes, the system dynamically updates friction estimates based on real-time slip angle comparisons, allowing vehicle control to adapt to changing surface conditions while maintaining operational efficiency.
3Measurement precision
If slip angles are compared between different surface conditions, then surface friction differences can be determined, but additional data processing requirements increase system complexity
Solution Approach 1:
The system extracts only the essential slip angle parameter from complex vehicle operation data for friction determination. By focusing specifically on slip angle comparisons rather than processing all available sensor data, the system achieves accurate friction determination while minimizing processing complexity and computational requirements.
Data Source
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AI summary
A computer system is disclosed for determining a difference in surface friction between a first set of surface conditions and a second set of surface conditions, the computer system comprising processing circuitry configured to receive first data corresponding to a first set of surface conditions, the first data comprising a first slip angle for at least one wheel of a vehicle, receive second data corresponding to a second set of surface conditions, the second data comprising a second slip angle for at least one wheel of a vehicle, compare the first slip angle and the second slip angle, and upon there being a difference between the first slip angle and the second slip angle, determine that a surface friction associated with the first set of surface conditions is different from a surface friction associated with the second set of surface conditions, wherein a lateral acceleration of the vehicle associated with the first data is substantially the same as a lateral acceleration of the vehicle associated with the second data.