In order to improve the ride comfort of the vehicle,the DRNN neural network PID was used to control the vehicle hydraulic suspension system,and the control performance indexes were simulated.A 1/4 sketch model of vehicle hydraulic suspension was established.The dynamics equations of the vehicle suspension system were deduced by secondorder differential equation,and a doubletube hydraulic shock absorber model was designed.The flow characteristics of main and auxiliary hydraulic cylinders were analyzed,and the DRNN neural network PID control method was adopted.The control effect of the vehicle hydraulic suspension system was simulated by using MATLAB software in the course of driving with random waveform interference,and compared with the traditional PID control method.The results show that in the vertical direction of vehicle hydraulic suspension system,the tire displacement,body displacement and body acceleration are larger by using traditional PID control method;while in the vertical direction of vehicle hydraulic suspension system,the tire displacement,body displacement and body acceleration are smaller by using DRNN neural network PID control method.Using DRNN neural network PID control mode,the parameters of the vehicle hydraulic suspension system can be adjusted adaptively,the interference of complex road conditions on vehicles can be reduced,and the ride smoothness and comfort can be improved.