Road Friction Estimation via Recursive Least Squares
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Solution Overview
Problem
Current methods lack an accurate and real-time estimation of the road surface friction coefficient, essential for optimizing vehicle stability control systems, as direct measurement is not feasible, and existing estimation techniques rely on pre-programmed data that may become irrelevant due to changing road conditions.
Innovation Solution
A computer program product and apparatus that utilize recursive least square estimation and a lookup table to calculate a lookup value based on detected vehicle parameters, such as the partial derivative of yaw rate or normalized lateral forces, to accurately estimate the road surface friction coefficient in real-time, enabling dynamic adjustments for improved stability control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pre-programmed data is used for estimation, then the system can provide initial stability control, but the data becomes irrelevant when road conditions change
Solution Approach 1:
The system transitions from static pre-programmed data to dynamic real-time estimation. The friction coefficient is continuously updated based on current vehicle parameters (yaw rate, lateral acceleration, steering angle) through recursive least squares estimation, allowing the system to adapt to changing road conditions while maintaining reliable estimates.
Solution Approach 2:
The system implements feedback by continuously comparing actual vehicle behavior (measured yaw rate and lateral acceleration) with predicted behavior based on the current friction coefficient estimate. This feedback loop allows the system to detect deviations caused by changing road conditions and update the friction coefficient estimate accordingly, maintaining both adaptability and reliability.
2Measurement precision
If direct measurement of friction coefficient is implemented, then accurate real-time data can be obtained, but the system complexity and cost increase significantly
Solution Approach 1:
Instead of directly measuring the friction coefficient, the system uses intermediary measurements of easily obtainable vehicle parameters (yaw rate from gyroscopes, lateral acceleration from accelerometers, steering angle from steering sensors). These intermediary measurements are then processed through mathematical models to infer the friction coefficient, achieving precise estimation without complex direct measurement equipment.
Solution Approach 2:
The system replaces potential mechanical direct measurement devices with computational methods. By using existing vehicle sensors and mathematical estimation algorithms (recursive least squares), the system achieves accurate friction coefficient measurement without adding complex mechanical measurement apparatus, thereby reducing overall system complexity while maintaining precision.
3Measurement precision
If real-time estimation algorithm is computed continuously, then accurate friction coefficient can be obtained, but computational load and processing time increase
Solution Approach 1:
The system applies partial action by updating the friction coefficient estimate only when necessary, based on triggering conditions such as changes in vehicle operating state or deviation thresholds. Instead of continuously recalculating the estimate at every possible moment, the system performs updates selectively, reducing computational load while maintaining sufficient accuracy for stability control applications.
Solution Approach 2:
The system uses preliminary action by pre-calculating and storing lookup tables that contain pre-computed friction coefficient values based on vehicle parameters. During real-time operation, the system can quickly retrieve or interpolate from these pre-computed tables rather than performing full recursive least squares calculations, significantly reducing computational load while maintaining estimation accuracy.
Data Source
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AI summary
A computer program product, a method and an apparatus for detection of road surface friction coefficient for vehicle stability control are disclosed. The computer program product comprises stored instructions for receiving detected vehicle parameters from a vehicle; calculating a lookup value based on the detected vehicle parameters, the calculating comprising an recursive least square estimation; retrieving a road surface friction coefficient from a lookup table by matching the calculated lookup value to the road surface friction coefficient stored in the lookup table; calculating adjustments to the vehicle using the road surface friction coefficient; and outputting the adjustments to a vehicle control system for execution.