Improved Vehicle Vibration Control through Optimization of Suspension Parameters Using the Response Surface Method and a Non-Linear Programming with a Quadratic Lagrangian Algorithm

Abstract

Vibration-control techniques generally fall into two categories: passive methods that optimize the structure of the suspension to absorb any impact from the ground, and active methods that directly control the vertical force of the suspension by hydraulic or electric actuators when the vehicle traverses a bumpy road. In this study, a vibration-control method is described that employs both an optimal controller and suspension parameter optimization. Continuous speed bumps are implemented to simulate more complex and realistic driving conditions. First, a vehicle system is modeled using a semi-recursive multibody formulation, which allows for a more precise description of the longitudinal–vertical dynamics. Then, an optimal control method for vehicle vibration control is introduced. Second, the Latin hypercube design is utilized to analyze the response surface methodology (RSM) model. For suspension optimization, the RSM model and the non-linear programming with a quadratic Lagrangian (NLPQL) algorithm are employed. Thirdly, both passive suspension optimization and active motion control are employed for vibration control. The results indicate that the presented method can effectively control vehicle vibration, decreasing the average vibration by 30.8%. The results suggest that the novel approach can also enhance the ride comfort in autonomous vehicles traversing, e.g., a series of speed bumps.

Parameter Optimization of Vibration Reduction Structure for Low-Speed, Multi-Acting Cam Ring Motor

“…The results of the variance regression model analysis are shown in Table 2 [19][20][21][22][23]. Table 3 shows that the lack of fit is not significant when the P of the model is less than 0.0001, indicating that the equation is significant.…”