Real-Time nonlinear predictive controller design for drive-by-wire vehicle lateral stability with dynamic boundary...

Area of Science:

• Automotive Engineering
• Control Systems
• Robotics

Background:

• Drive-by-wire technology enhances vehicle stability but introduces transmission delays.
• Existing control strategies may struggle with unpredictable delays and complex driving conditions.

Purpose of the Study:

• To develop a nonlinear model predictive control (NMPC) strategy for vehicle stability control.
• To compensate for random transmission delays inherent in drive-by-wire systems.
• To improve vehicle handling and lateral stability under extreme conditions.

Main Methods:

• Combined nonlinear vehicle dynamics with driver behavior to define a stable region for yaw rate and sideslip angle.
• Designed an NMPC controller to track reference values within the identified stable region.
• Simulated the controller using CarSim/Simulink and validated with hardware-in-the-loop experiments.

Main Results:

• The proposed NMPC controller effectively tracks desired yaw rates and suppresses sideslip angles.
• The controller demonstrated superior performance under low adhesion road conditions.
• Dynamic boundary conditions within the NMPC improved tracking accuracy and stability suppression.

Conclusions:

• The NMPC strategy successfully improves vehicle stability and compensates for transmission delays.
• The approach enhances vehicle handling and lateral stability in challenging driving scenarios.
• The method is validated through comprehensive simulations and experiments.