Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation

Area of Science:

• Automotive Engineering
• Control Systems
• Mechanical Vibrations

Background:

• Vehicle suspension systems are crucial for ride comfort and handling dynamics.
• Optimizing suspension performance requires adapting to diverse road conditions and driving scenarios.
• Existing active suspension systems often struggle to balance conflicting performance objectives.

Purpose of the Study:

• To develop and validate a multi-mode switching strategy for active vehicle suspension.
• To enhance vehicle dynamic characteristics, focusing on comfort, safety, and integrated performance.
• To optimize control parameters using advanced algorithms for superior performance.

Main Methods:

• Utilized the least squares method for road space domain height estimation.
• Constructed an active suspension control mode switching model based on road estimation.
• Employed Particle Swarm Optimization (PSO) to tune Linear Quadratic Regulator (LQR) control weights.
• Analyzed vehicle dynamic characteristics through simulation and experimental testing.

Main Results:

• Achieved road estimation accuracy with an overall error of less than 2% compared to detection ruler methods.
• Demonstrated superior performance of the multi-mode switching strategy over passive and traditional LQR control.
• Validated the system's ability to balance driving comfort with handling safety and stability.

Conclusions:

• The proposed multi-mode switching active suspension strategy offers a significant improvement in vehicle dynamics.
• Intelligent mode switching enhances the overall driving experience by adapting to real-time conditions.
• This approach provides a more comprehensive and intelligent solution for active suspension control.