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The present work investigates the effect of magnetorheological fluid (MRF) on limited slip differential (LSD) system for automotive applications to improve torque distribution which influences traction and maneuverability. The proposed differential system uses a magnetorheological fluid which permits to control the locking torque effectively and then improve the vehicle traction characteristics. To evaluate the proposed system, a prototype model involves some rotating clutches submerged in MRF associated with an electromagnet coil was built. Experimental tests were carried out in two cases, first case by applying mechanical force on the friction clutches and the second by applying magnetic field to change the MRF viscosity. The yield stress of MRF depends on the magnetic field applied by the electromagnet by varying electric current. The controllable yield stress generates friction force on the rotating clutches surfaces to transmit torque.

In this paper, a fuzzy-PID controller is applied in a half vehicle active suspension system to enhance vibration levels of vehicle chassis and passenger seat. The fuzzy-PID controller consists of fuzzy and PID connecting in a series manner, the fuzzy output is considered as the PID input. Genetic Algorithm (GA) is selected to tune controller parameters to obtain optimal values that minimize the objective function. The equations of motion of five-degrees-of-freedom active half-vehicle suspension system are derived and simulated using Matlab/Simulink software. Double bumps and random road excitations are used to study the performance of suspension systems including bounce and pitch motion. The performance of the active suspension system using optimized fuzzy-PID controller is compared with conventional passive to show the efficiency of the proposed active suspension system.

In this paper, a nonlinear semi-active vehicle suspension system using MR fluid dampers is investigated to enhance ride comfort and vehicle stability. Fuzzy logic and fuzzy self-tuning PID control techniques are applied as system controllers to compute desired front and rear damping forces in conjunction with a Signum function method damper controller to assess force track-ability of system controllers. The suggested fuzzy self-tuning PID operates fuzzy system as a PID gains tuner to mitigate the vehicle vibration levels and achieve excellent performance related to ride comfort and vehicle stability. The equations of motion of four-degrees-of-freedom semi-active half-vehicle suspension system incorporating MR dampers are derived and simulated using Matlab/Simulink software.

Proportional-integral-derivative (PID) controller is effective, popular and cost effective for a lot of scientific and engineering applications. In this paper, PID and fuzzy-self-tuning PID (FSTPID) controllers are applied to improve the performance of an active seat suspension system to enhance the pregnant woman comfort. The equations of motion of thirteen-degrees-of-freedom (13-DOF) active seat suspension system incorporating pregnant woman body model are derived and simulated. PID gains are tuned and estimated using genetic algorithm (GA) to formulate GA PID controller. In FSTPID, fuzzy logic technique is used to tune PID controller gains by selecting appropriate fuzzy rules using Matlab/Simulink software. Both controlled active seat suspension systems are compared with a passive seat suspension. Suspension performance is evaluated under bump and random road excitations in order to verify the success of the proposed controllers.