中文版本

Opportunity

Active suspension systems are crucial for enhancing vehicle ride comfort and driving safety. However, existing systems face significant challenges, including nonlinear coupling, unavoidable disturbances, slow convergence rates, and high energy consumption. Traditional control methods, such as decoupling control, dynamic inversion, and robust control, often treat nonlinear coupling and disturbances as entirely harmful, leading to suboptimal performance. These methods either fail to utilize beneficial coupling/disturbance effects or require precise model knowledge, which is difficult to obtain for uncertain systems. Additionally, current bio-inspired reference models for active suspension systems overlook the impact of nonlinear damping and stiffness, resulting in poor control efficiency. These limitations motivate the development of a more efficient and robust control method that leverages beneficial coupling and disturbances while ensuring finite-time convergence and reduced energy consumption. 

Technology

The patent introduces an innovative control method for active suspension systems based on second-order sliding mode technology. The method involves:  

1. Dynamic Modeling: Deriving a suspension travel dynamics equation that includes disturbance information and a tire travel dynamics equation.  
2. Coupling and Disturbance Analysis: Establishing a coupling term equation and a sliding surface equation to transform the tracking error dynamics into sliding mode dynamics.  
3. Nonlinear Disturbance Observer: Constructing an observer to estimate disturbances and evaluating their effects using a disturbance effect indicator.  
4. Beneficial Coupling Utilization: Introducing a coupling effect indicator to assess whether coupling terms are beneficial or harmful to system performance.  
5. Controller Design: Building a target trajectory tracking controller using second-order sliding mode methods, which actively utilizes beneficial coupling and disturbances while suppressing harmful ones. The controller ensures finite-time convergence, improved robustness, and reduced energy consumption.  

Advantages

• Improved Performance: Enhances ride comfort and handling by effectively utilizing beneficial coupling and disturbances.  
• Energy Efficiency: Reduces control energy consumption through bio-inspired reference models and optimized control inputs.  
• Robustness: Handles parameter uncertainties and external disturbances more effectively than traditional methods.  
• Finite-Time Convergence: Ensures faster stabilization of the suspension system compared to asymptotic approaches.  

Application

• Automotive Industry: Implementation in passenger cars, commercial vehicles, and high-performance sports cars to improve ride quality and safety.  
• Autonomous Vehicles: Integration into self-driving car systems for better stability and comfort.  
• Heavy Machinery: Use in construction and agricultural vehicles to mitigate vibrations and enhance operator comfort.  
• Military Vehicles: Application in armored vehicles to improve off-road performance and crew comfort.