Grey human simulated intelligent control of magnetorheological semi-active and electromagnetic active seat suspension

Abstract The semi-active seat suspension has limited effect on vibration suppression in the low-frequency band, while the active seat suspension has excessive energy consumption and is prone to system instability due to improper control in the higher frequency band. To achieve more reliable vibration reduction effects of the seat suspension system in a wider frequency band, this paper integrates an electromagnetic active actuator and a magnetorheological (MR) damper into the seat suspension, and adopts the human simulated intelligent controller (HSIC) algorithm to achieve a hybrid control of active and semi-active. Combined with grey prediction, it can to some extent compensate for the response delay of the actuators. In this paper, the dynamics of the seat suspension system is modelled by the Lagrange method, which also includes the mechanical performance analysis of the two actuators. Subsequently, the mechanical property and response time of the MR damper are tested. Finally, the corresponding simulation and experiments of the designed controller are carried out. The results show that the grey HSIC can effectively improve the ride comfort of the seat suspension under road excitation in different frequency bands. This research also provides a reference for the subsequent suspension control of multiple actuators.