Control Research of Nonlinear Vehicle Suspension System Based on Road Estimation

The control parameter of the semi-active suspension system varies with road profile; therefore, in this study a new algorithm based on cuckoo search (CS) optimization method and road estimation was proposed to investigate the characteristics of the nonlinear parameters and at the same time improve the riding comfort. Based on this, a seven degree of freedom full vehicle model was developed with nonlinear damper and spring. The sprung mass acceleration, pitch acceleration, and tire deflection could be selected as the objective functions, and the control current of semi active suspension was selected as optimization variable. A multi-object CS algorithm was utilized to obtain the optimal parameters under different road profiles, and a road estimation algorithm was used to identify the road level. Then the control parameters could be adjusted adaptively according to the level of the road. Furthermore, computer simulations were carried out to illustrate the performance of the proposed algorithm. Simulation results indicate that the proposed algorithm can easily identify the road level and adjust the control parameters adaptively. Moreover, the CS algorithm can provide better control performance compared to Particle Swarm Optimization (PSO).