S. Mirzaei, M. Saghaein - Nejad, V. Tahani and M. Moallem,
Volume 20, Issue 2 (4-2001)
Abstract
This paper introduces a novel passive suspension system for ground vehicles. This system is based on a flexible Electromagnetic Shock Absorber (EMSA). In the proposed system, efforts are made to a) select a high damping coefficient usable in a car b) determine Physical dimensions and geometry not much different from those of the mechanical shock absorbers and c) seletct EMSA weight and volume low enough for the core not to be saturated. A model is designed and developed followed by determining the dynamic equations for the model. The results from the simulation in a quarter car model are then compared with those from passive and active suspension systems.
Keywords: Active Suspension Systems, Electromagnetic damper, Finite Element method
Z. Z. Ahangari Sisi, M. Mirzaei, S. Rafatnia, B. Alizadeh,
Volume 39, Issue 2 (2-2021)
Abstract
Active vehicle suspension system is designed to increase the ride comfort and road holding of vehicles. Due to limitations in the external force produced by actuator, the design problem encounters the constraint on the control input. In this paper, a novel nonlinear controller with the input constraint is designed for the active suspension system. In the proposed method, at first, a constrained multi-objective optimization problem is defined. In this problem, a performance index is defined as a weighted combination of the predicted responses of the nonlinear suspension system and control input. Then, this problem is solved by the modified firefly optimization algorithm to find the constrained optimal control input. To evaluate the performance of the proposed method, the results of the unconstrained and constrained controllers are provided and discussed for various road excitations. The results show a remarkable increase in the ride comfort with the limited force, while other suspension outputs including the suspension travel and tire deflection being in the acceptable ranges. In addition, these controllers are compared with Sliding Mode Control (SMC) and Nonlinear Model Predictive Control (NMPC) in the presence of model uncertainty.
