Active Downforce Control for Tire Grip and Vehicle Stability
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Solution Overview
Problem
Existing vehicle systems lack an effective method to determine the desired tire grip for active downforce control, which is crucial for maintaining stability during various driving scenarios, particularly under uncertain road conditions.
Innovation Solution
A method integrating feedforward and feedback controls, utilizing sensor data and aerodynamic actuators, to calculate and adjust the necessary tire grip by fusing stability criteria such as axle, wheel, and body stability, and employing neural networks or fuzzy logic for precise control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If active downforce control is implemented to maintain vehicle stability during motion, then vehicle stability is improved, but the complexity of the control system increases due to the need for multiple sensors, aerodynamic actuators, and complex control algorithms
Solution Approach 1:
The control system is segmented into distinct functional modules: feedforward control module that calculates requested normal forces based on tire friction circle, feedback control module that determines normal force adjustments based on stability criteria, and fusion module that combines both controls. This modular segmentation manages system complexity by organizing the control architecture into manageable, independent components that can be developed and tuned separately.
Solution Approach 2:
The feedforward control calculates the requested normal forces at each axle in advance based on predicted driving conditions and tire friction characteristics. This preliminary action allows the system to proactively adjust downforce before stability issues arise, rather than reacting to them, thereby improving vehicle stability while maintaining manageable control complexity through predictive rather than purely reactive control.
2Reliability
If multiple stability criteria (axle stability, wheel stability, body stability) are integrated into the feedback control, then the robustness against uncertainties is improved, but the computational complexity and control algorithm difficulty increase
Solution Approach 1:
Multiple stability criteria (axle stability, wheel stability, body stability) are merged into a unified feedback control framework. The feedback control module integrates these different stability considerations simultaneously to determine the requested normal force adjustments, allowing the system to maintain robustness against various uncertainties while managing algorithmic complexity through a cohesive control structure rather than separate independent controls.
Solution Approach 2:
The system implements comprehensive feedback control that continuously monitors actual vehicle behavior against desired stability criteria and adjusts the normal forces accordingly. This feedback mechanism improves robustness by automatically compensating for uncertainties in road conditions, tire characteristics, and vehicle dynamics, while the structured feedback architecture keeps the control algorithm manageable through systematic error correction.
3Speed
If feedforward control using tire friction circle is used to determine requested normal forces, then the responsiveness to driving conditions is improved, but the accuracy of tire grip determination deteriorates under uncertain road conditions
Solution Approach 1:
The feedforward control module calculates the requested normal forces in advance based on the tire friction circle model and current driving conditions. This preliminary calculation provides rapid responsiveness to changing driving scenarios. The system then refines this preliminary determination through feedback control that adjusts for actual vehicle behavior, thereby maintaining both responsiveness and accuracy under uncertain road conditions.
Solution Approach 2:
The feedback control module determines adjustments to the feedforward requested normal forces based on actual vehicle stability performance and observed tire grip characteristics. This feedback mechanism corrects inaccuracies in the feedforward tire grip determination while preserving the rapid responsiveness of the feedforward control, achieving both speed and precision in the overall control system.
Data Source
AI summary
A method for downforce control includes receiving sensor data from sensors, using a feedforward control to determine a first requested normal force at the first axle of the vehicle and a second requested normal force at the second axle of the vehicle and the sensor data, using a feedback control to determine a first requested normal force adjustment at the first axle of the vehicle and a second requested normal force adjustment at the second axle of the vehicle using the sensor data, fusing the first requested normal force at the first axle of the vehicle with the first requested normal force adjustment to determine a first-adjusted normal force request at the first axle, and fusing the second requested normal force with the second requested normal force adjustment to determine a second-adjusted normal force request at the second axle.