Active Downforce Control for Vehicle Drifting Maneuvers
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Solution Overview
Problem
Current active downforce systems hinder or prevent drivers from performing intentional vehicle maneuvers like drifting by maximizing traction, which is not suitable for certain driving conditions.
Innovation Solution
A system and method for drift detection and control that includes determining an intentional drift probability based on occupant inputs, using feedback and feedforward control systems to adjust aerodynamic actuators, allowing controlled loss of traction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If active downforce systems maximize traction through aerodynamic elements, then vehicle grip and stability are improved, but the ability to perform intentional drifting maneuvers is hindered or prevented
Solution Approach 1:
The active downforce system dynamically adjusts aerodynamic element positions based on detected driving conditions. During normal operation, elements provide maximum downforce for grip. When drift conditions are detected (through sensors monitoring steering angle, lateral acceleration, and vehicle dynamics), the system dynamically reduces downforce or adjusts aero bias to allow controlled drift, thus adapting to different maneuver requirements
Solution Approach 2:
The system changes key parameters including downforce magnitude, aero bias distribution (front/rear balance), and actuator positions based on detected drift conditions. By modifying these parameters in response to sensor inputs, the system transitions between high-grip normal driving and reduced-traction drifting modes, resolving the contradiction between maintaining grip and enabling drift
2Productivity
If aerodynamic actuators are continuously adjusted to maintain optimal traction, then vehicle performance is improved, but system complexity and control requirements increase
Solution Approach 1:
The control system continuously receives feedback from sensors monitoring steering wheel angle, lateral acceleration, wheel speeds, and other vehicle dynamics parameters. This feedback loop enables the system to detect drift conditions and automatically adjust aerodynamic actuator positions accordingly, maintaining optimal performance without requiring complex manual intervention
Solution Approach 2:
The system autonomously detects drift conditions through sensor data and self-adjusts aerodynamic element positions without requiring direct driver input or external control. The control algorithm automatically determines when drift conditions exist and modifies downforce distribution accordingly, reducing the burden on the driver and simplifying the user interface
Data Source
AI summary
A method for drift detection and control for a vehicle may include determining an intentional drift probability of the vehicle based at least in part on one or more occupant inputs. The method further may include determining an initial aero bias upper bound using a first control system. The method further may include determining an initial aero bias command using a second control system. The method further may include determining a final aero bias upper bound based at least in part on the intentional drift probability, the initial aero bias upper bound, and the initial aero bias command. The method further may include controlling one or more aerodynamic actuators of the vehicle based at least in part on the final aero bias upper bound and the initial aero bias command.