Performance and Behaviour of a Magneto-Rheological Damper in a Semi-Active Vehicle Suspension and Power Evaluation
[1]
Ahmed Shehata Gad, Automotive Engineering Department, Helwan University, Cairo, Egypt.
[2]
Helmy Mohamed El-Zoghby, Automotive Engineering Department, Helwan University, Cairo, Egypt.
[3]
Walid Abd El-Hady Oraby, Automotive Engineering Department, Helwan University, Cairo, Egypt.
[4]
Samir Mohamed El-Demerdash, Automotive Engineering Department, Helwan University, Cairo, Egypt.
Magneto-rheological (MR) dampers play a vital role in semi-active vehicle suspension systems because of their many advantages in terms of safety, performance, reliability, and if the control units in a semi-active suspension fail, the MR dampers will continue to work as a passive system. Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy techniques are highly useful for the modelling and control of magnetorheological (MR) dampers. The variable damping force produced by an MR damper depends on the conjunction between two controllers. So, this paper focuses on the design of these controllers. First, a fuzzy self-tuning PID controller based on the tuning of a classical PID controller is used as the system controller to determine the desired damping force. Second, an Adaptive Neuro-Fuzzy Inference System (ANFIS) inverse model is used as the basis for the damper controller, which produces the voltage to be applied to the MR damper. A vehicle suspension model with four degrees of freedom (4 DOFs) together with the MR dampers is derived. The semi-active control units, namely, the fuzzy self-tuning PID controller and the ANFIS inverse model controller, are designed. Simulation results indicate that the proposed semi-active technique based on MR dampers with ANFIS inverse model damper controllers and fuzzy self-tuning PID system controllers is able to achieve ride comfort and dynamic stability more than that of a semi-active technique based on MR dampers with signum function damper controllers (SFDC) and fuzzy self-tuning PID system controllers, and a conventional passive suspension system. The dissipated and controlled powers are estimated of passive dampers and MR dampers both front and rear axles. Control performance criteria are evaluated in the frequency and time domains in order to quantify the suspension effectiveness under random road disturbance and bump excitation.
Vehicle Suspension, Magnetorheological Damper, Fuzzy Self-Tuning PID, ANFIS Forward Model, ANFIS Inverse Model
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