Armored vehicle typically always experience poor road conditions,which seriously affect the comfort of passengers and drivers.This article takes an armored vehicle as the research object,establishes a 13 degree of freedom overall dynamic model of armored vehicle seat human body,and uses commercial software RecurDyn to simulate and verify the established dynamic model.With the goal of improving the ride comfort of drivers and passengers,a fuzzy PID control strategy is designed to obtain the expected output load of the seat semi-active suspension.The reverse model is trained using a BP neural network to convert the expected load into the control current of the magnetorheological damper in the seat semi-active suspension,achieving load adjustment of the semi-active suspension control,thereby improving the ride comfort of drivers and passengers.Simulation analysis was conducted on sinusoidal and random road surfaces,and the results showed that under sinusoidal road conditions,the pelvis acceleration response amplitudes decreased by 20.83％,18.12％,18.46％,and 19.40％at frequency of 4.0,5.0,6.3,8.0 Hz,respectively.Under E-level random road conditions,semi-active suspension reduces the root mean square values of seat and pelvis acceleration by 19.15％and 18.00％,Under F-level random road conditions,semi-active suspension reduces the root mean square values of seat and pelvis acceleration by 19.35％and 18.37％,respectively.Therefore,the designed fuzzy PID control strategy for seat semi-active suspension can effectively improve the comfort of drivers and passengers.
维普
万方数据
