Research For The Vehicle Hydraulic Semi-Active Suspension System Based On Immune-Particle Swarm Optimization Algorithm

With the development of technology and the improvement of people's living standard, the people are also getting higher requirement to the handling stability and riding comfort of automobile, it has become one of the important issues of modern automobile research that how to enhance vehicle's safety and comfort. This topic aims to research the macpherson semi-active suspension by immune-particle swarm control algorithm, after debuging repeatedly, obtaining suspension system's immune-particle swarm control technology, the technology is used to improve the system's dynamic and static characteristics, enhances the riding comfort and driving stability and provides the reference to the study of the intermediate and senior vehicle hydraulic semi-active suspension product development.Firstly, this article carries on the analysis to the suspension's classification and structure, selects the macpherson semi-active suspension system which has universal application as the research object. Refering the related literature, establishing the three degree-of-freedom 1/4 vehicle suspension mathematical model for the first time, which integrates the vertical damping model and lateral vibration damping model, and infering the suspension dynamic equation and the equation of state. Then semi-active suspension system entity model is established by using ADAMS software, in view of the fact that the suspension system mathematical model and the entity model's error, using the least square method to identify the suspension's various parameters. After the identification ADAMS output response curve and the MATLAB output curve tallies basically, which has completed the preparation work for the suspension system control policy's research. The immune-particle swarm control algorithm is proposed for the first time which suits the suspension system, designing immune-particle swarm optimization controller, and useing this method in suspension system's control. The simulation result has indicated that the semi-active suspension system's dynamic characteristic compared with uncontrolled suspension system has improved effectively which based on immune-particle swarm algorithm, sharpened the system's anti-interference ability as well as parameter time-variance robustness. Comparing the simulation result with suspension system's fuzzy control system and the optimal control system, the result shows that the semi-active suspension system's immune-particle swarm control quality is better than the fuzzy control quality and the optimal control quality.Adopting ADAMS and MATLAB co-simulation to verify the imm-une-particle swarm algorithm for semi-active suspension control strategy accuracy, the result shows that the suspension system model based on co-simulation tends to be coincide with mathematical model, obviously, the design of the immune-particle swarm algorithm control strategy is accurate and feasible.Finally,designed the inertial channel semi-active suspension actuator, established mechanical control model, and deduced mathematical model. In order to study changes in cross-sectional area of inertia channel affect the system's dynamic property, carring on the simulation using MATLAB software to the system, the result indicates:(1)At low frequency, the system's dynamic damping and dynamic stiffness changes at larger, at high frequency, each value becomes smaller and stable, it can provide low frequency big damping force and high frequency small damping force to the semi-active suspension system.(2) With the increase of inertia channel cross-sectional area, actuator dynamic stiffness and dynamic damping peak value also increase along with it, obviously, the size of the inertia channel cross-sectional area has great impact on the system dynamics.(3)In the high-frequency phase, force transmission rate tends to be coincided, it can significantly reduce the vehicle's vibration when driving on uneven pavement and improve driving stability.