Wheel Friction Estimation Using Tire Model Uncertainty Bounds
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Solution Overview
Problem
Conventional methods for estimating road friction lack the ability to provide a measure of uncertainty, which is crucial for reliable vehicle control systems, as they often operate with incomplete or imprecise knowledge of tire and operating conditions.
Innovation Solution
The method involves using a range of tire models, including a lower bound and upper bound model, to estimate a friction uncertainty value based on actual tire-related sensor signals, such as slip, traction force, and temperature, to quantify the reliability of friction potential estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional friction estimation methods are used, then the estimation process is simple, but the reliability of the friction potential estimate is insufficient due to lack of uncertainty measure
Solution Approach 1:
The system performs preliminary actions by obtaining a range of tire models before friction estimation, using these models to calculate uncertainty bounds, and then applying this uncertainty information to improve the reliability of the friction potential estimate in subsequent control decisions
Solution Approach 2:
The patent introduces tire models as an intermediary element between the friction estimation process and the reliability assessment. These models serve as mediators that translate sensor inputs into uncertainty measures, enabling the system to quantify estimation reliability without fundamentally redesigning the entire estimation architecture
2Measurement precision
If a single tire model is used for friction estimation, then the calculation is fast and simple, but the measurement precision of the friction potential is insufficient
Solution Approach 1:
The patent segments the tire model usage into multiple distinct models (at least two different tire models) rather than relying on a single model. This segmentation allows the system to compare results across different models and derive uncertainty measures, thereby improving measurement precision through diversified model perspectives
Solution Approach 2:
The system changes parameters by using multiple tire models with different characteristics and assumptions. By varying the model parameters and structures, the patent enables more precise friction estimation through comparison and uncertainty analysis, while managing complexity through systematic parameter variation
3Measurement precision
If multiple tire models are used to improve estimation accuracy, then the measurement precision increases, but the device complexity increases
Solution Approach 1:
The patent extracts only the essential uncertainty information from multiple tire models without requiring the full complexity of each model to be actively used in real-time control. By taking out and focusing on the uncertainty bounds derived from model comparisons, the system achieves improved precision while managing computational complexity through selective information extraction
Data Source
AI summary
Methods, computer program products and apparatuses for estimating the uncertainty of a friction potential value of a wheel of a vehicle are disclosed. The method for estimating the uncertainty of a friction potential value of a wheel of a vehicle comprises obtaining a range of tire models (72). The method further comprises receiving a sensor signal (74) indicative of at least one actual tire-related value. Finally, a friction uncertainty value is calculated (76) based on the received sensor signal and the range of tire models. The friction uncertainty value is indicative of the uncertainty of the friction potential.