Autonomous drift controller for distributed drive electric vehicle with input coupling and uncertain disturbance

Area of Science:

• Automotive Engineering
• Control Systems
• Robotics

Background:

• Autonomous vehicles require expanded dynamic control capabilities for advanced maneuvers.
• Drifting presents unique challenges due to vehicle instability and complex dynamics.
• Distributed drive electric vehicles offer a flexible platform for exploring novel control strategies.

Purpose of the Study:

• To develop a novel autonomous drift controller for distributed drive electric vehicles.
• To enhance the dynamic control envelope and application range of autonomous vehicles through drifting.
• To address system complexities like input coupling and uncertain disturbances in drift control.

Main Methods:

• Implemented a two-level control architecture: upper-level and lower-level controllers.
• Utilized control channel recombination to convert an over-actuated system into a standard square system.
• Designed a fuzzy-integral sliding-mode controller for the upper level, accounting for system uncertainties.
• Developed a lower-level controller to manage actuator dynamics and distribute virtual control inputs.

Main Results:

• The controller successfully enabled autonomous drift maneuvers in simulations and bench tests.
• Demonstrated fast response and strong robustness of the proposed control system.
• Validated the effectiveness of the control channel recombination and fuzzy-integral sliding-mode control strategies.

Conclusions:

• The novel autonomous drift controller significantly expands the dynamic capabilities of electric vehicles.
• The proposed control strategy is robust and provides fast responses, suitable for complex maneuvers.
• This research paves the way for more versatile and dynamic autonomous vehicle applications.