Abstract
The significant non-linearity and uncertainty in the behavior of magnetorheological (MR) suspension systems has been one of the main challenges in the application of this technology in the development of appropriate control algorithms. Here, four model-free control algorithms studied theoretically in prior work are applied to a full vehicle featuring four MR dampers and evaluated through road test to identify the most suitable control algorithm. The four model-free control algorithms include the well-known skyhook control, the hybrid control, the fuzzy logic control, and a newly proposed intelligent control algorithm, the human simulated intelligent control (HSIC). As the first step, four MR dampers (two for the front parts and two for the rear parts) are designed and manufactured based on the damping-force levels and mechanical dimensions of stock dampers of the test vehicle. After experimentally measuring the magnetic-field-dependent force property and controllability, a precise inverse model of MR damper is formulated. Subsequently, four controllers are developed and implemented using the rapid control prototyping technology. Then the road test with different control schemes is undertaken under various road conditions and vehicle speeds. For comparison purposes, the road test of the passive suspension system with four stock dampers is also carried out under the same conditions as that of the MR suspension system. Finally, the control responses for ride comfort and stability are evaluated in both time and frequency domains. The results support the conclusion made in the prior numerical analysis that the semi-active suspension system with each control algorithm can improve ride comfort and stability in some indexes, but HSIC algorithm is found to be the most suitable one with four MR dampers in the MR suspension system.
Get full access to this article
View all access options for this article.