Adaptive Braking Control via Dynamic Adhesion Model
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Solution Overview
Problem
Existing braking control methods for vehicles rely on predetermined optimal slip rates, which may not correspond to varying friction conditions on the road, leading to potential wheel lock-ups and reduced braking performance.
Innovation Solution
An adaptive braking control method that regularly readjusts an adhesion model to reflect current friction conditions, using measurements of wheel speed and braking torque to predict and adjust the braking setpoint within a given prediction horizon, ensuring the slip rate remains optimal and preventing wheel lock-up.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a predetermined optimal slip rate is used for braking control, then the control system is simple to implement, but the braking performance deteriorates when road friction conditions vary
Solution Approach 1:
The patent implements dynamic adaptation of the adhesion model parameters based on real-time wheel behavior observations. The system transitions from a static predetermined slip rate to a dynamic model that continuously updates its parameters to match current road conditions, resolving the contradiction between system simplicity and braking reliability under varying conditions.
Solution Approach 2:
The adhesion model performs self-calibration by observing wheel slip behavior and automatically adjusting its parameters without external intervention. This self-service mechanism allows the system to maintain high braking performance across different road conditions while keeping the overall control architecture relatively simple.
2Reliability
If the adhesion model is regularly readjusted to match current track conditions, then the braking reliability is improved, but the computational complexity increases
Solution Approach 1:
The system uses feedback from actual wheel slip behavior to continuously refine the adhesion model parameters. By observing the relationship between applied braking torque and actual wheel slip, the system adjusts its model to better predict future behavior, improving reliability while maintaining computational efficiency through iterative refinement.
Solution Approach 2:
The predictive nature of the approach allows the system to pre-adjust braking torque based on forecasted wheel slip behavior. By anticipating future slip conditions and adjusting braking accordingly, the system improves reliability while distributing computational load over time rather than requiring intensive real-time calculations.
3Productivity
If a fixed adhesion model is used for prediction, then the calculation is computationally efficient, but wheel lock-up may occur when the model does not match actual track conditions
Solution Approach 1:
The patent transforms the static adhesion model into a dynamic one that adapts its parameters based on observed wheel behavior. This allows the system to maintain computational efficiency while accurately reflecting current road conditions, preventing wheel lock-up that would occur with mismatched fixed models.
Solution Approach 2:
The system changes the parameters of the adhesion model based on observed wheel slip characteristics. By adjusting parameters like peak friction coefficient and optimal slip ratio according to actual conditions, the system maintains both computational speed and accuracy in predicting wheel behavior across different track conditions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly enhances braking reliability by accounting for real-time road conditions, reducing the risk of wheel lock-up and improving braking performance across different surfaces.
Implementation Method 1
an adhesion model representative of a relationship between a coefficient of friction and a rate of slip
Data Source
Figure 1~2
Figure 3~4
AI summary
The invention relates to a braking control method for a vehicle comprising several wheels (1) carrying tires (2) and equipped with brakes (4), the control comprising the generation for each wheel of a braking setpoint (Cf,cons) in response to a braking command, comprising the steps of, for each wheel: - regularly recalibrating an adhesion model (Ca/C0 = fq1...qn(τ)) representative of a relationship between a coefficient of friction (µ) and a slip rate of the wheel (τ); - using the regularly recalibrated adhesion model and its characteristic shape to establish in a given prediction horizon an evolution of the braking setpoint which, while responding to the braking command and its predictable evolution during the prediction horizon, respects a given calculation constraint (τ); - retaining as the value of the braking setpoint a value of the evolution thus determined corresponding to a first step of calculation of the prediction horizon.