Abstract:

In this paper， an adaptive wheelbase preview robust H_∞ control method is proposed based on vibration based road roughness recognition to address the impact of unknown road surface input on the control effect of active suspension. By collecting the vibration acceleration response of the wheels through real vehicle experiments， the longitudinal road surface roughness information is identified based on the vibration based road surface roughness detection method of the front wheels. A speed adaptive wheelbase preview method is designed to obtain the delay relationship of the road surface excitation received by the front and rear wheels of the vehicle， providing real vehicle data for the wheelbase preview control of the rear wheel suspension. On this basis， a multi-objective speed adaptive wheelbase preview robust H_∞ control method considering motion constraints is designed， and the optimal solution of parameters in linear matrix inequality （LMI） is achieved through multi-objective genetic algorithm （MOGA） to improve control accuracy. The experimental and simulation results show that the method proposed in this paper can accurately identify road roughness information and effectively improve suspension performance indicators and vehicle vibration frequency， effectively suppress vibration within the frequency range sensitive to motion sickness， and balance passenger driving experience while meeting driving smoothness requirements. Meanwhile， this method also provides a new approach for vertical vibration control of multi axle vehicles.

Key words: road roughness recognition, active suspension, adaptive wheelbase preview, robust H_∞ control, motion sickness