Vehicle Friction Estimation via Trajectory Segmentation
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Solution Overview
Problem
Existing methods for estimating the coefficient of friction between a vehicle's wheels and the underlying surface are imprecise and lack robustness due to inaccuracies in measurement variables, leading to variable and unreliable estimates.
Innovation Solution
A method and device that decompose the vehicle's trajectory into individual curve segments, estimate lateral forces and slip angles using a one-track model, and adapt a tire characteristic curve to these values to accurately estimate the coefficient of friction for each segment, storing these estimates in a coefficient of friction map for improved accuracy and robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods are used to estimate the coefficient of friction, then the estimation process is simple, but the measurement precision and reliability are poor due to inaccuracies in measurement variables
Solution Approach 1:
The trajectory is decomposed into multiple individual curve segments, and the coefficient of friction is estimated separately for each segment. This segmentation allows the system to process complex trajectory data in manageable portions, improving measurement precision while keeping each individual estimation step relatively simple
Solution Approach 2:
The trajectory is pre-decomposed into curve segments before estimation, and tire characteristic curves are pre-adapted for each segment. This preliminary processing organizes the data structure in advance, enabling more accurate friction estimation without requiring complex real-time computations during the actual measurement phase
2Reliability
If a single overall estimation is performed, then the process is fast, but the reliability is low due to variable estimates across different trajectory regions
Solution Approach 1:
By dividing the trajectory into multiple curve segments and estimating friction for each segment individually, the system achieves more reliable and consistent results across different driving conditions. Each segment's estimation is independent and robust, avoiding the variability that occurs in single overall estimations
Solution Approach 2:
The method adapts tire characteristic curve parameters to match the specific conditions of each curve segment. By adjusting these parameters locally for each segment rather than using a single global model, the system achieves higher reliability and consistency in friction estimation across diverse trajectory regions
Data Source
AI summary
A method and a device for estimating coefficients of friction of a wheel of a vehicle with respect to an underlying surface including decomposing a supplied trajectory into individual curve segments, estimating a lateral force and a slip angle for a front axle of the vehicle, assigning respectively estimated lateral forces and slip angles relating to the associated individual curve segments and storing these value pairs in a memory, estimating a tire characteristic curve for each of the curve segments based on the value pairs stored for the respective curve segment in the memory, estimating a coefficient of friction for each curve segment based on the respectively estimated tire characteristic curve, and storing the estimated coefficients of friction relating to the respectively associated curve segments in a coefficient of friction map.