Research On Intelligent Control Strategy For Automotive Active-suspension

As the automotive technology advances, the suspension system experienced passive suspension, semi-active suspension to active suspension changes. The design of the suspension system is more and more complex, and the performance is required higher and higher. Although active suspension has not been popular for now, it will become mainstream in the future along with the cost reduction and the development of control technology, automobile electronic technology and new energy technology, because of its superior comprehensive performance.A good control strategy has critical influence to full optimal properties of active suspension. The traditional control methods (skyhook control, PID control, sliding mode control, etc.) have many advantages of maturity, easy realization, low hardware requirements, etc., but they remain to be further improved in the stability, robustness and control effect.Intelligent control method has become an intensive research topic and a mainstream of modern control, with the improvement of the intelligent algorithm theory. In order to refine the intelligent control methods for active suspension and increase comprehensive properties of suspension system, this thesis conducts a research on intelligent control strategy for automotive active-suspension and mainly includes following several aspects.(1) Firstly, the simplification and modeling of automotive suspension system are discussed. Mathematics models of the half car 4-degree-of-freedom and the quarter car 2-degree-of-freedom are established, respectively. The differential equations of motion and state-space expressions of each model are given. Road excitation is divided into two different conditions:vibration and impact, which be studied respectively. The specific expressions of time domain road input in different conditions are present.(2) An active suspension model based on PID-FUZZY control is built. The half car model has four degrees of freedom, subject to irregular excitation from a road surface. The control is the sum of PID and fuzzy-logic control. PID control uses the vertical acceleration of vehicle as the input source, fuzzy-logic control uses the rotary acceleration and velocity as the input source. The simulation results show that the active suspension is effective in vibration isolation of vehicle body.(3) An active suspension system for vehicles using fuzzy-pid control is proposed. The half-car model treated here is described by a nonlinear system with four degrees of freedom, subject to excitation from a road surface. The active control is fuzzy-pid control, and the control is determined from the view-point of ride comfort, minimizing the vertical and rotary acceleration of vehicle body. In the derivation of fuzzy control rules, vertical velocity and acceleration of the vehicle body are denoted as the input variables. The simulation results indicate that the proposed active suspension performs effectively when compared with other forms of control.(4) An active suspension for the quarter car 2-degree-of-freedom model using a fractional PIλDμcontroller is present. The active control is expressed as the summation of PIλand PDμthat choose vertical acceleration of the body and suspension deflection as input variable, respectively. The parameters of the controller are optimized using the genetic algorithm (GA). The simulation results indicate that the fractional PIλDμcontroller for suspension system is effective in the vibration isolation of the vehicle body and has better performance than classical PID controller.(5) In order to verify the control effect of the control strategy proposed in this paper, the hardware in the loop simulation test platform based on the dSPACE real time system is built. The road input and states of the suspension system will be simulated in high precision by using the HIL test platform, which has advantages of simple structure, short time for ready and low test cost. The effects of the intelligent control strategy and fractional PIλDμcontrol algorithm are verified by the hardware in the loop test platform, the performances of suspension system are improved evidently. The HIL test also provided important reference for the further research of active suspension control system.