Research On Control Algorithm Of Vehicle Semi-active Suspension Based On Attitude Compensation And State Observation

Due to excessive road excitation,rapid acceleration/deceleration or high-speed steering during the running of vehicle,the body attitude of vehicle will be unstable,which results in a loss of ride comfort and cargo integrity.And attitude control with semi-active suspension can reduce the degree of loss,but not all the feedback signals required for control can be measured by sensors.Thus,suspension state observer is needed to estimate the relevant signals.Due to the damping saturation of semi-active suspension,the suspension parameters may change,which will affect the estimation accuracy of state observer.To solve the above problems,this paper designed the control algorithms of semi-active suspension based on attitude compensation and state observation.Since the control parameters would affect the ride comfort and handling stability of vehicle,the control targets of semi-active suspension were divided and the control parameters under different control targets were determined.The main research contents of this paper include:Firstly,the controlled object model was established.According to the data of the chassis of the test vehicle,the semi-active suspension model of the vehicle was established in Adams/Car and the simulation communication foundation with Simulink was set.The polynomial model was established based on the test data of the external characteristics of MR dampers.Simultaneously,four-wheel random pavement based on wheel-track characteristics and long-slope bump pavement excitation model were established.And time-domain excitation was transformed into spatial excitation which was introduced into Adams.Secondly,the control algorithms of semi-active suspension based on attitude compensation and state observation was designed.The semi-active attitude compensation control algorithm was designed with the hierarchical architecture control theory and the control algorithm of magnetorheological(MR)damper was designed based on the output damping range of MR damper.And considering the saturation of MR damper,the state observer of vehicle suspension was structured.The control targets of semi-active suspension were classified and the genetic algorithm was used to optimize the control parameters under each control target.Finally,the effectiveness of the semi-active suspension control algorithm was verified.The application of Adams and Simulink co-simulation was used to analyze the signal estimation effect of the state observer,attitude compensation control effect and control target partition effect respectively.The hardware-in-the-loop test was carried out,and the test results were compared with simulation results to verify that the results of the semi-active suspension control algorithm running in the ECU are consistent with the simulation results.The results showed that the estimation accuracy of the state observer is accurate,and the estimation error of suspension speed can be controlled within 0.01m/s after stabilization.Semi-active suspension with attitude compensation control based on the speed signal estimated by the state observer can ensure the vertical control effect and restrain the body posture effectively.When the control targets are divided,the semi-active suspension achieves the best comfort in comfort mode,the best stability in sport mode and the most balanced performance in comprehensive mode.