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Application of a Preview Control with an MR Damper Model Using Genetic Algorithm in Semi-Active Automobile Suspension
Technical Paper
2019-01-5006
ISSN: 0148-7191, e-ISSN: 2688-3627
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Automotive Technical Papers
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English
Abstract
A non-linear mathematical model of a semi-active (2DOF) vehicle suspension using a magnetorheological (MR) damper with information concerning the road profile ahead of the vehicle is proposed in this paper. The semi-active vibration control system using an MR damper consists of two nested controllers: a system controller and a damper controller. The fuzzy logic technique is used to design the system controller based on both the dynamic responses of the suspension and the Padé approximation algorithm method of a preview control to evaluate the desired damping force. In addition, look-ahead preview of the excitations resulting from road irregularities is used to quickly mitigate the effect of the control system time delay on the damper response. Adaptive neuro-fuzzy inference system (ANFIS) inverse model without preview, ANFIS inverse model with preview, and ANFIS inverse model with preview and optimization strategies are used to design the damper controller to evaluate different values of the command voltage based on the tracking of a desired damping force to compare which of them gave the best behavior of the MR damper. Each one of these strategies is used in conjunction with the system controller to evaluate the effectiveness of a damper controller design on semi-active control. Control performance criteria are evaluated in the time and frequency domains in order to quantify the suspension effectiveness under bump and random road disturbance. The simulation results prove that the proposed strategy of the ANFIS inverse model with preview and optimization on MR damper produces a smoother and lower input voltage to the MR damper coil, ensuring extended damper life and lower power requirement, respectively. The compared results reveal that although the ANFIS inverse model with preview and optimization is able to improve ride comfort and vehicle stability over other mentioned strategies for semi-active suspension system or even passive suspension system.
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Citation
Shehata Gad, A., El-Zoghby, H., Oraby, W., and Mohamed El-Demerdash, S., "Application of a Preview Control with an MR Damper Model Using Genetic Algorithm in Semi-Active Automobile Suspension," SAE Technical Paper 2019-01-5006, 2019, https://doi.org/10.4271/2019-01-5006.Data Sets - Support Documents
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