| In recent years, with the development the national technology and economic, the car has become the indispensable transport tools in the life, with the development of the economic and improved quality of life, the requirements of car’s performance are also increasing. As an important part of the car the performance of suspension system directly determine the car’s ride comfort, driving stability and safety. Because the stiffness and damping coefficients of passive suspension can not be adjusted and the active Suspension is very complex and costly, and the damping coefficient of Semi-active Suspension can be adjusted and its structure is simple, cost lowly, stable performance much more stable, so semi-active suspension system has become a hot topic in today’s industry.Magnetorheological damper is a controllable damper which has lots of characteristics such as simple structure, fast response and low energy consumption, It can suppress the vibration of the car well in a variety of road conditions by using this technology and then impacting the performance of vehicle suspension damping. In practical applications, the magneto-rheological dampers get the control power by the core control algorithm of controller. Fuzzy-PID control algorithm combines the simply structure, adjustable features of the PID algorithm and the flexibility and adaptability advantages of fuzzy control method, it is very suitable to be used in the automotive semi-active suspension system.The semi-active suspension system based on magnetic damper is the research object of this article. Respectively establish the kinetic model of magnetic damper and the two DOF 1/4 model of vehicle suspension and do the fuzzy PID control on Suspension systems. By forming a closed-loop feedback between the magnetorheological damper based on BP neural network inverse model and fuzzy PID controller to achieve semi-active control of vehicle suspension, In order to improve the performance of the suspension damping system. In the research, firstly establish the kinetic model of magnetic damper and the two DOF 1/4 model of vehicle suspension, laid the foundation for the control of semi-active suspension. Secondly, using the car vertical velocity and acceleration as the input of fuzzy controller, using the three parameters as the output of the fuzzy controller, using the adjustable damping force of semi-active suspension system as the output of fuzzy PID controller, and then implement the fuzzy PID control algorithm in MATLAB/Simulink software. In order to make the damper output a damping force which close to the desired control force, we need to simulate the input current which the reverse dynamic characteristics predicted.int order to get this input current, we can use the powerful learning ability of BP neural network and establish magnetorheological damper neural network model. Finally, combine the inverse model, fuzzy PID controller and the suspension system to achieve a closed loop control of semi-active vehicle suspension and then do the simulation analysis.1) when the road excitation is the random road input and impact, the magnetorheological semi-active suspension car based on fuzzy PID control has better ride comfort and handling stability by simulating and comparing the passive suspension, semi-active suspension PID control and fuzzy PID control; 2) by the simulation of different road impact condition, verify that the design of fuzzy PID control magnetorheological semi-active suspension is much more some stable.In summary, the fuzzy PID control method of automotive magnetorheological semi-active suspension system can effectively improve the ride comfort and handling stability of the car, and has a certain validity and superiority. |
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