Ride Comfort Optimization Method for Commercial Vehicle Based on Nonlinear Damping and PSO

This paper proposes a nonlinear optimization approach for the ride comfort based on nonlinear damping to improve the optimized reliability of ride comfort of the commercial vehicle. First, a vibration model of a commercial vehicle is established and followed by a road excitation model and a nonlinear damping model that can provide nonlinear damping force by using compression velocity rather than linear force. The weighted Root Mean Square (RMS) from previous comfort models is then obtained and compared with experimental data. The result indicates that the ride model based on nonlinear damping leads a more accurate result and is closer to the experiment than the model based on the equivalent one. A optimization approach for ride comfort based on nonlinear damping to the commercial vehicle is further proposed. The sum of weighted RMS of the vertical vibration acceleration of driver seat at 30 km/h, 60 km/h, and 90 km/h is taken as the objective function with the stiffness and nonlinear damping gradient of suspension as the design variables. Afterwards, the particle swarm optimization (PSO) is utilized to improve the ride comfort. And the optimal stiffness and nonlinear damping are obtained. Finally, the effectiveness of the presented approach is evaluated by the comparison of the logarithmic power spectral density and the weighted RMS before and after optimization. It is shown that the optimization method can reduce the average peak of power spectral density and the average weighted root mean square by 29.9% and 10.2%, respectively.